Performance of a Mobile Car Platform for Mean Wind and Turbulence

Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , , ; 1986 Martin , ; Open Access and Mahrt ć 2004 i š , Martínez et al. ; Discussions Lenschow Belu 2005 Techniques Atmospheric Atmospheric , Measurement Isaac et al. ; 2000 , Patton et al. ; ects of the car motion are shown to 3 ff 1997 , 950 949 , and N. J. Tapper Williams and Marcotte 2 ; ([email protected]) ć Vickers and Mahrt i š 1991 ). One alternative is research aircraft observations, which have ). This is particularly evident in the stable ABL, where motions , 2013 2012 , , , D. H Lenschow ). The aircraft sizes and configurations vary considerably. Recently there 1 ć i š 2011 Kang et al. Mahrt et al. , ; ; This discussion paper is/has beenTechniques under (AMT). review Please for refer the to journal the Atmospheric corresponding Measurement final paper in AMT if available. Monash University, School of Mathematical Sciences,National Melbourne, Center Victoria, for Australia Atmospheric Research,Monash Boulder, University, Colorado, School USA of Geography and Environmental Science, and Cooperative ments are taken either attion single is points rarely or met along in reality vertical ( towers. However, this assump- 1 Introduction Horizontal homogeneity is a frequentlyboundary used layer assumption (ABL). in It studies is of used the atmospheric out of necessity, because a majority of the measure- tower. The corrections requiredbe to smaller remove and the simpler e thancan the therefore corrections satisfactorily for measure researchequipment. aircraft near-surface Other measurements. turbulence natural A advantages using of car relatively aany car, low-cost time such of as the day ability or to nightmake drive and it on follow applicable any the to road terrain at observations slope,with of as the a well usual variety as platforms, of its such low flow as cost regimes of research that operation, aircraft cannot or be networks achieved of flux towers. The lack of adequatelayer near-surface spatial observations structure of motivatedturbulence the measurements. the stable The development calibration atmospheric and of boundary performed validation an of using the instrumented controlled car field measurements car are experiments for and mobile a comparison with an instrumented Abstract Atmos. Meas. Tech. Discuss., 7, 949–978,www.atmos-meas-tech-discuss.net/7/949/2014/ 2014 doi:10.5194/amtd-7-949-2014 © Author(s) 2014. CC Attribution 3.0 License. 1 2 3 Research Centre for Water Sensitive Cities, Melbourne, Victoria,Received: Australia 6 December 2013 – Accepted: 17Correspondence January to: 2014 D. – Belu Published: 30 JanuaryPublished 2014 by Copernicus Publications on behalf of the European Geosciences Union. from various origins aresignals superimposed that at are a often associated measurement with point turbulence intermittency and (e.g., result inreceived complex considerable attention over the last several decades (e.g., Tjernström and Friehe et al. 2012 has been a focus on instrumenting and using light and unmanned aircraft for ABL 2010 Performance of a mobile carmean platform wind for and turbulence measurements D. Belu 5 20 15 25 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , ). Raab Gordon 1998 , Mayer et al. Straka et al. ). The instru- ; Mahrt 1998 2011 , , Mahrt ; 1994 , culty maintaining constant height Metzger et al. ffi ; 2008 er considerable improvements in measur- , ff ). The car-mounted instruments are always 952 951 ) used instrumented cars for measuring atmo- s between the desired spatial coverage and re- ff 1997 , 2010 ( Mann and Lenschow ). Albeit aircraft o Smith et al. 2013 , Vickers and Mahrt ) and ) studied the complex flow in the Sierra Nevada mountains using a sim- van den Kroonenberg et al. 2002 ) seem to have been the first to install three-dimensional sonic anemome- ( 2008 ( 2012 Vellinga et al. ) report on the mobile mesonet, a mobile system for observing mesoscale ( Aircraft cannot fly below ationary certain or speed, a while mobile a platform. car can operateCar as motions either are a more sta- less constrained contamination and of smaller the than measured aircraft wind motions, by resulting platform in motions. at the same height above the ground andAircraft are not experiments influenced have by shown turbulentestimating motions. that surface flying fluxes ( as low as possible is preferable for Aircraft can be vertically displacedaltitude by variations. turbulent motions, Similarly, resulting aircraftabove in varying have uncontrolled terrain. di Thesedients height of variations, atmospheric together variables, canseries with result (e.g., mean in vertical artificial gra- fluctuations in aircraft time ments can be mounted onabout a 4 car m within above a the few ground. tenths of a meter of the ground up to Small unmanned aircraft, somecompared to of a which car. can flyAircraft at are night, much have moretime, limited expensive which payload to necessitates trade-o deploy. Thispeated may flight patterns result needed in for limited reducing the airborne random flux error ( Low-level aircraft measurements area predominantly car restricted can to measurestable daytime, ABL. at while nighttime as well. This is critical for observations of the ; – – – – – – – Using instrumented cars for atmospheric measurements is not new. Instrumenting a car with turbulence sensors provides a new capability for measuring 1996 ( research (e.g., easily mounted on awith car. the A front lattice of aluminiumThe the frame latter frame is significantly reduces additionally attached vibrations braced to ofsensors to the roof is frame. the racks The located car frame’s of 1.2 attachment m bumper a point in with for car, front steel of guy the wires. car bumper and 3 m above the ground surface, 2 Instrumented car measurements 2.1 Instrumented frame The motivation was to develop a simple low-cost instrumented platform that can be ilar system, additionally equippedet with al. a two-dimensional sonicters anemometer. on a road vehicle. Theyan studied instrumented the truck. enhancement of However, a turbulencean on detailed instrumented highways examination car using of for the measuringundertaken general ABL previously. Here applicability mean we of wind show andsurements that of turbulent the an fluxes horizontal has instrumented mean not car and been can turbulence be structure of used the for ABL. mea- spheric thermodynamic properties in complexand terrain, Mayr excluding the wind vector. weather phenomena. Theple mobile standard mesonet meteorological consists variables,Mayr including of et the al. instrumented horizontal cars wind that vector, every sam- 1 s. low-level horizontal ABL structure that complementsways: existing techniques in the following 2012 ing spatial structure of thein ABL, they certain have situations. a One number critical ofbe case limitations very is that prevent the shallow, their stable and use ABLhorizontal because has flight it tracks. strong occurs vertical at night, gradients can that require almost perfectly level 5 5 25 20 15 10 15 10 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | horizontally car V ). The development is the GPS-INS motion 2.2 INS V erence between the sonic and set by the smaller amplitude of ff ff . 2 is the heading. The final wind vector in is obtained from , is obtained by rotating Ψ V ter V 954 953 shows the frame and instrument placement on a car. 1 axis aligned with the local Earth gravity. The GPS-INS is z (northward, eastward, downward) = Ψ ) Ψ , (1) is the the car-relative flow vector measured by the sonic anemometer. ter sin INS w cos , − V , (2) sonic ter − V Ψ is the wind vector in the car coordinate system, Ψ v car , V car ter tc sin cos sonic V u V M ( = = = = The typical procedure for obtaining the final wind vector from the current system is The frame can be attached to a wide variety of cars; a dedicated car is not neces- A low-cost miniature GPS-aided inertial navigation system (GPS-INS; IG-500N, SBG tc ter ter car V V where M is the two-dimensional rotationthe matrix, local and meteorological coordinate system the following. We assume herethe that local the terrain departures coordinatenate of system the system are car negligible. defined coordinate Then byusing system the the the from wind local heading vector information: terrain, in the coordi- which are then aligned withtor the in car the coordinate car system.GPS-INS coordinate This velocities: means system that is the a wind simple vec- vectorV di where vector, and The current GPS-INS isordinate factory system, configured unlike such the thatcoordinate typical it system INS outputs with systems the velocity that inmounted output such its velocity that own in its co- the coordinate system geographic is aligned with the sonic’s coordinate system, 2.2 Determining the wind vector an unshielded type Eare fine used in wire this thermocouple system. (TC) Figure 12.7 µm (0.0005 inch) in diameter which is within the legal limits in Victoria, Australia. A CSAT3 sonic anemometer and the entire system and start the measurements. sary. In order to simplifyattached the to mounting a of set the30 frame min of on to roof a attach racks. car, the Itments the roof frame are takes racks is installed two to permanently after a people the car to and frame carry the is the guy attached wires frame, to to and a the car, less bumper. so than Some it instru- takes about 1 h to set up turbulence measurements. The somewhat lowerto accuracy more of expensive such airborne systems INScar compared motions. systems The is GPS-INS partially data are o of recorded at the 20 accelerometers Hz. and The internal gyroscopesries sampling is frequency of 10 internal kHz, which filters is tothrough downsampled 100 the Hz, through on-board and a extended then Kalman se- filter. mergedtion Since with of the the accelerometer final GPS output and signal is gyroscopeexternal based sampled data, on corrections. at small integra- 4 The Hz initial GPS errorsresults. is can The grow used GPS rapidly is to without also provide used such to provide long-term the stability heading. to the final Systems) is attached to theentation sonic of the anemometer sonic. to The providesonic GPS-INS measurements, the and data position, to are speed rotate used the andtem to wind ori- to vector remove measured the the in car meteorological theof motions car coordinate small coordinate from system sys- low-cost the GPS-aided (defined INS in has Sect. made this type of inexpensive system feasible for The sonic and TC datasonic are is recorded 60 at Hz. 20such Additional Hz. as instruments The surface internal temperature, could water sampling be vapour, frequency and installed of CO to the measure other variables, 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). The ). ), in the 2 1 2001 , ). While this three- ). 2008 , ter Wilczak et al. w − , ter ). The maximum driving time for u ). There were 20 tracks, and the , 2 2 ter v ( = ). The range of those manoeuvres that the horizontal wind vector. h 956 955 1986 (see Table , 1 − van den Kroonenberg et al. , (3) ; ∆Ψ Lenschow 1986 h car , V + , (4) h INS INS V w Lenschow + ∆ + ∆ (eastward, northward, upward) = ) h sonic sonic w denotes the error and superscript , the surface heat flux was positive, and sky was covered with scattered stra- V w , 1 v ∆ − , u = ∆ = ∆ ( h w The tower was equipped with the same instruments as the car (a CSAT3 sonic and Using the two-dimensional rotation simplifies the determination of the error propa- = V ∆ Two field tests wereas performed the to flow detect distortion and inducedwind correct by vector. the various The car sources tests andvres of were frame, for errors, designed and in-flight such to to validate calibration mimic the the ( corrected typical final research aircraft manoeu- 3 Field tests gravity. In this way, themately wind aligned vector with is localnormally flow given streamlines, achieved in which by the for using coordinate stationary tilt system sonic correction that anemometers algorithms is is (e.g., approxi- V Note that eastward, northward,rain, and upward so or that downward, the are local relative vertical to is the determined local ter- by the slope of the terrain rather than by by a simple permutation of components: a type Eground) fine and wire was located TC 25 with m from a the 12.7 road µm near one diameter) end at of the the tracks same (Fig. height (3 m above the each track was 1 min. Thethe length lower of car the speed. firstanalyses, two The except tracks lengths for reached of the only 780 spectral allthere m calculations. other the because The road tracks of length is will of relatively be flat 900 m limited and is homogeneous. to chosen 900 m because in further 3.1 Test 1: repeated passes andThe tower first comparison test wasria, conducted Australia in on a rural 61.5 ms relatively December flat-terrain 2012, area from neartocumulus 12:23 Shelford, cloud. Victo- to The 13:03 LST. instrumenteda The car relatively winds passed flat were a and about tower homogeneous driving road back (see and Fig. forth along car. An additional limitationatmosphere occurs above the for ABL, thetime, which calibrations these is that limitations obviously are require unachievable compensated for flyingplicity for of the by in car the car. the motions reduced At compared amplitude calm theenough to and data same the greater for aircraft, sim- calibrating so the the car two observations. tests performed here provide car speeds ranged from 13 to 27 ms could be performed by thecomplicated car is responses limited, to because many changing of pitch, them depend lift on or the aircraft speed, none of which occur for the where of the GPS-INS andfollowing way: sonic, which are provided by the∆ manufacturer (Table natural alignment with thecompared local to terrain research slope aircraft. is Aircrafttated observations an have into advantage to of the be the three-dimensionally globalby ro- instrumented gravity meteorological car (e.g., coordinate system,dimensional transformation with can be the used for vertical thecases, car such determined as as well, in we perform the it validation only test in specific where the cargation. is The driven accuracy over of speed the bumps. final wind vector is obtained from the nominal accuracies alignment with the localthat road are slope not followed is by notcorrections the only desirable airflow. This for to could small-scale the befield road high-wavenumber addressed tests part irregularities by discussed of applying pitch the below and spectra, show roll but that the these results corrections from are the usually very small. This 5 5 25 20 15 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | . is 1 − with ects ff 1 sonic − v averaged ects from ff sonic u becomes zero for all w ). This linear dependence ◦ erent tracks and the tower. ff during this manoeuvre. This 1 − so that ◦ erences between ff 1.3 − ects of the flow distortion or misalignment of 958 957 ff ) for the two tracks should be equal to the car sonic in small circles with the radius of 20 m on the top of erent speeds (e.g. to force equal time intervals for all u 1 ff − erent sizes of large eddies retained in flux calculations, which ff usually performed in the steadyof atmosphere nonstationarity above and the horizontal ABL heterogeneity.the to This car reduce may system the be because e more of of the an proximity issue of for the surface. The horizontal wind speedwind is velocity corrected for by anyposite assuming two directions. the If consecutive stationarity so, tracks ofthe the driven the car average at true of coordinate same the systemspeed. longitudinal car ( The car-relative speeds measured flow in data speedover op- shows in two that consecutive the tracksso di and they the are car forced speedzero to are in zero. a the The data, function samecalibrating so of average aircraft a the measurements. of correction The car the is caveat speed, lateral here not is component required. that This these is manoeuvres a are standard procedure in The data show that therelative vertical wind wind speed speed (the hasis mean a removed linear angle by dependence of the onspeeds. attack the coordinate is car- rotation 1.3 of – – Another manoeuvre was performed during this test, where the car was driven at were performed in order tosensors: reduce the e 4 Correction and validation of car4.1 measurements Corrections The car, the frame andabout the ten sensors times induce higher flowmodify than distortion. the the Since total the true measured carror wind speeds wind in speed, were vector the the and magnitude flow is distortion of likely can the to significantly measured cause longitudinal the wind only component. Two significant corrections er- could be due to alag phase in shift the between the GPSnot internal response, be INS accurate which and during points GPS sharpexcluded resulting to from turns. from the As the a analyses. a limitation time result, that the the data for current all system significant turns may will be speed-bump crossings were made, driving at a constant car speeda of constant about speed 12 of ms abouta 8 parking ms garage. Thethe usual final corrections wind failed vector, tofrom but remove an the independent were GPS car-motion successful locatedA e when in comparison the the between car horizontal the ratherderestimated car two than the speed from instruments horizontal was the showed car miniature taken that speed GPS-INS. the by miniature about GPS-INS 2 ms un- The second test was16 conducted August on 2013, a fromstrong windy 10:30 turbulence day and to positive in surface 11:30 LST. heat Melbourne,and flux. The Victoria, forth The wind instrumented Australia along car at on was a 3 driven m street back was with around several 4 speed ms bumps. Eight tracks with the total of 27 3.2 Test 2: speed bumps Changing the track lengths fortracks) di would result in di is undesirable. with higher car speeds.tracks The over reasons the for 900 m, this andlatter are the the is same spatial approximate important scales homogeneityenergy for because of containing calculating the region there turbulent at fluxes. is larger The same scales. a Using spatial the significant scales equal track contribution are lengths used to means that for the the comparison fluxes between from di the 4.2 Comparison of averages and fluxesAveraging with intervals the for tower themeans car that data there is are a taken smaller number to of data be points equal (i.e., shorter to time the interval) for track tracks lengths, which 5 5 25 15 20 10 25 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ) ) 5 the and erent L 1986 fluxes w ff ( 0 w 0 u ): ). They found 0.10, where the 1994 erence increases , = 2012 ff | ( vw r cient sampling and the | flux appears as if it has ffi 0 w 0 fluxes start to exhibit a very v Lenschow and Stankov 0 ) that will be discussed below. Burns et al. 2 0 w 0.07, and 0 v ), the Taylor hypothesis gives the Lenschow et al. or a component of the horizontal u 3 = the flux integral length scale, | T f uw L r | erent approaches to correcting the flow cient ( ff flux seems to agree the best. However, ffi 0 v 0 cient between the vertical wind speed (see Fig. 960 959 ). 0.55, u ffi 1 = − | 2012 set resulting from the nature of sonic anemometer ). This is a result of the small sample size for the wT , ff 5 r | , (5) 2 / 1 ! 2 ), who find that random sampling errors are smaller for scalar ws , and tracks 18 and 19 for r 2 the random flux error, ws 2 0 r is either the temperature + u F 1 Aubinet et al. the correlation coe 1994 s σ ( erence is not caused by instrument errors, but probably by nonsta-

. In this study, ff ws v r = ) or | L ( flux does not look realistic, because the values oscillate around zero for u F , where erent directions. Such behaviour could result from two mechanisms: flow | F 0 shows the comparison between all components of the car and tower fluxes shows the comparison between the car and tower mean wind and tempera- ff s σ w is the flux, 4 3 0 2 / u 1 F cient sample size. Tests with several di f Lenschow et al. ffi L L This conclusion is further supported by the analysis of The car momentum fluxes generally are the right order of magnitude, but the agree- For each track, the tower data are averaged over 5 min for the comparison of mean Figure Figure 2 the car ning version 4 ofresults confirm the the firmware. speed-dependent We underestimation of use the the sonic same temperature. ment CSAT3 on firmware a version, point-to-point andthe basis our opposite is sign questionable. The from car the tower. The the source of the error in the underestimation of the sonic temperature by CSAT3 run- variables and over 10 minmined for by requiring the that fluxes. the Thecar same 10 and spatial min tower scales, averaging fluxes. or Since for eddy thethe the sizes, largest mean are fluxes scales present wind is in for speed the deter- both car is the measurements about are 1.5 900 ms m, and tower fluxes and theTherefore, related a provisional loss conclusion of is thatis overlapping the related between possible to problem consequent the with flux small the car sample estimates. size, rather than to uncorrected flow distortion. similar behaviour to the car (Fig. and tracks in di distortion that has notinsu been completely corrected, ordistortion the have not random changed errorthe this resulting tower behaviour. from However, fluxes when is the decreased averaging interval to for 2 min, the tower fluxes than for momentumrandom error fluxes. of This fluxes on is the a correlation coe consequence of the dependence of the overbar denotes the average over all tracks. The term on the right hand side of Eq. ( a variable wind speed, where track length, and tracks compared to the car.car These measurements caveats with should the be tower. considered when comparing the ture data for each track. Thecar agreement is can satisfactory be for used all variables, forvirtual implying measuring that temperature mean the has horizontal a structuremeasurements typical of (e.g., o the ABL. The mean sonic from the TC temperature, but thewith correlation the is good. car-relative The flow heat-flux speed. di by the This CSAT3 is anemometer in consistent strong with winds the reported overestimation by of heat flux that the car willof have 10 min. driven This about numberReducing six decreases the to or tower about averaging seven three even tracks further tracksdata when would during would result 5 a not min in be averaging insu single is representativefluxes tower of used. have average the a mean considerable flow. overlap, Likewise, yielding consecutive smoother 10 min flux tower estimates between di (tracks 14 and 15The for car somewhat underestimates the temperatureimplying variance that for the both di the sonictionarities and TC, in tower measurements.car The car heat heat fluxes fluxes calculated agree from well with the the sonic tower. temperature The are systematically larger than corresponding time scales ofsen 10 instead min. of The 10 5 min min because averaging the for interval mean of variables a is single cho- car track is 1 min, which means and variances. All three speed variances generally agree well, except for certain tracks 5 5 15 10 20 25 15 10 25 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | – ), 7 2 law, 3 / 5 − k component show v , points to a similar 2 0 u ). The magnitudes of random . There is also an increase of the 1986 0 . The random error for variances is , which means that all tower spectra component for this experiment, be- , w 1 5 0 − v v , and it appears only for the 2 min tower . The spectra for the 2 0 4 and v 4 , but is variable in the data. This is because ◦ 962 961 erent for the four groups of tracks (see Table in Fig. ff 0 erent. The car spectra are therefore averaged for ff T 0 w agree well with the tower, as well as with the T Lenschow and Stankov and w , u filter to remove the high frequencies where spurious oscillations occur. ff shows the lateral velocity spectra in the frequency domain for the car- shows the spectral agreement between the car and tower measurements. 7 for track 18 that resembles the car 6 2 0 v Frequency spectra for all three components in the car coordinate system (Figs. Figure Figure Furthermore, the agreement of the other two momentum fluxes is improved when ) also illustrate the relative importance of the frame motion and attitude corrections. each group, yielding four spectra for each variable. the wavenumber ranges are also di The car spectra for which implies that the standardincrease corrections with work the well. car The speed.almost spectral Since certainly amplitudes the results slightly car from speed theflux increases small with with increase time, successive in as runs, variance seen this due from to e.g., the increasing heat comparable. The integral scale isto calculated by the integrating first the zero autocorrelation crossing function ( is thus 5 to 7 times larger for momentum than for heat flux, while the integral scales are 9 A concern was that high-wavenumbertributions road irregularities to could introduce the spurious con- final wind, because the three-dimensional rotation is not used to GPS-INS. The phase shift shouldthe be spectral 180 peaks areadequately so resolved. close One solution to of thebut this the sampling issue throughput could frequency of be the that to GPS-INSapply the does use a not a phase cut-o currently higher shift allow sampling that. is rate, Another not approach is to measured wind and theare GPS-INS-measured approximately motion. the The samecause lateral the as car component the track spectra northward orientationThe has characteristic only peaks a at smallquency deviation about for from 7 wind the Hz and east-west GPS-INS, for and direction. thecar are lateral speeds. also at This component approximately implies are the that same atThe frequency these reason the for spectral all why same peaks these are fre- vibrations causedthough are by the not the GPS-INS removed frame recorded after vibrations. them, the is standard found corrections, in even the phase shift between the wind and distinct peaks at largethe wavenumbers. These wavenumber peaks domain, are whichrather a than points function spatial to of modes. the their car local speed origin in as frequency oscillations ual car tracks, lookspectrum. very Since similar the car for speeds each are di variable, so they are averaged into a single tower all 1 min long, unlike 900of m data from points previous for sections. calculation ThisThe of is final spectra, to shapes which ensure simplifies the ofspeed same the the for number analysis spectra all and tower are comparison. spectra nothave is the very taken same to sensitive wavenumber be to range. 1.5 ms this Individual tower choice. spectra, The corresponding mean to wind individ- error are given by the error bars in Figs. conclusion that the anomalous variancesthat are are due to not propagating adequately mesoscale sampled structures by both the tower4.3 and car. Comparison of spectra with theThe tower spectra are calculated incar the and wavenumber domain the for tower. The the input comparisonusing time between the series the car-relative are transformed flow from speedtower the for time spectra the to assuming car space domain spectra, the and applicability the of mean the wind Taylor speed hypothesis. for The the car tracks are averaging. This indicates thattracks could the result apparently fromreduced overestimated short-lived by car larger strong variances averaging mesoscale for intervals eventsfor some for tracks whose the 14 magnitudes and tower are 15, fluxes. where Inspection the of car the considerably raw overestimates data obtained in the same way as for the fluxes. 2 min tower averaging is used, particularly for 5 5 25 15 20 10 25 15 20 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 950 , 2012. 959 variance over the speed . ects on the final results for 2 ff − w s 2 , 2 − s 2 erent from the aircraft measurements, ff 10.1029/2011JD016987 964 963 when the car is crossing the speed bumps after the cor- w variance over the flat road. This implies that for tracks over and is compared to: w 2 − s We thank Darren J. Hocking for his help with the design and construction 2 ) is used for correcting the wind when driving over the speed bumps. The , D. and Mahrt, L.: Is geometry more universal than physics in atmospheric boundary 2.2 ć i the variance before the corrections, 1.554 m the variance of the flat parts of the tracks, 1.302 m š – – The natural simplicity and low cost of operating such a system make it a useful layer flow?, J. Geophys. Res., 117, D09115, doi: and Data Analysis, Springer, Dordrecht, the Netherlands, 2012. in urban city canyons arenetwork not possible of with towers an – aircraft.an is A instrumented likely possible car. alternative to – be a considerably dense more expensive and less flexible than the mean vertical speed inducedto by the the flow meteorological distortion, coordinate and system. rotating the horizontal wind tool for studying nearrange surface turbulence of statistics applications suchrelaxed is as if fluxes limited the and only variances. instrumentedsuch by The frame as the horizontal is presence mapping mountedstructure, of of on and the a measuring a nocturnal horizontal road, four-wheel-drive stable gradients vehicle. ABL, which at probing Studies the can edges the also of stable forests, cold be within pool forests or because of the smaller amplitudethe and corrections fewer degrees for pitch of and freedom. rollvertical Unlike for are motions the negligible of aircraft, at the high instrumentsing frequencies, are while wind about the components three lateral even and timesmations for smaller that low-wind than have the speeds. to correspond- The be crucial performed corrections are: removing and the transfor- longitudinal car speed, removing corrections for obtaining the wind vector are smaller and simpler than for the aircraft, Sect. flow distortion. Other corrections havetypical small road to conditions. negligible e Thiswhere is both substantially the di attitude anglesto and the the wind aircraft vector, and motion must vector be are measured significant and4.4 compared removed to get the Speed true bumps wind. The three-dimensional rotation of the wind vector into the Earth coordinate frame (see wavenumber end are about antem order as of recorded magnitude by smaller thelocity. than GPS-INS, The which the spectra of translates motion GPS-INS to of motion aboutmeasured the itself three sys- wind. are times This an smaller order implies for ofcar that ve- magnitude the are smaller most than to the important remove corrections the for mean the car instrumented speed and the mean vertical speed induced by the correct for the attitude angles. The spectra show that their contributions at the high- Belu Aubinet, M., Vesala, T., and Papale, D.: Eddy Covariance: A Practical Guide to Measurement is sponsored by the National Science Foundation (NSF). References and Kais Hamza areFaculty of gratefully Science, acknowledged. Monash This University. The study National Center was for funded Atmospheric Research by (NCAR) an ECR grant from Acknowledgements. of the frame and field tests. Useful discussions with Larry Mahrt, Peter Isaac, Yanfei Kang, 5 Conclusions The instrumented carment presented to towers in and this aircraft for study measuring the is ABL mean a and feasible turbulence structure. alternative The and comple- tracks are divided into theflat parts parts. when the The car variance isrections of crossing is a 1.306 speed m bump, and the other, So, the appliedbumps corrections to the successfully value decreasebumpy of roads, the it may be advisable to use the full three-dimensional rotation. 5 5 25 20 15 10 10 15 20 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | , , 10.1175/1520- 10.1175/1520- 10.1175/1520- 10.1175/1520- 10.5194/amt-4- 10.5194/amt-4-705- 951 950 951 951 , 2013. , 2013. 952 10.1007/s10546-009-9436-9 AV, J. Atmos. Ocean. Tech., 25, er, D., and Zeeman, M.: Non- , 1998. , 2012. 2 ff 955 , , 2012. 951 959 952 950 952 ects of mesoscale surface thermal het- 960 ff 951 , 2008. , 2012. 956 , , 1996. 965 966 , 1991. , 2002. , 1994. 950 950 , 1994. 955 950 952 , 950 10.1175/1520-0469(1986)043<1198:LSITCB>2.0.CO;2 10.1007/s10546-012-9782-x 950 , 2012. , 2010. 10.1175/JTECH-D-11-00138.1 , 2004. 10.1007/s00703-010-0063-2 , 2008. , 2005. 10.1175/JAMC-D-11-0190.1 AV Carolo”, Atmos. Meas. Tech., 4, 705–716, doi: 2 10.1029/94JD00737 10.5194/amt-5-2095-2012 951 10.1175/2008JTECHA1114.1 950 961 , 2011. , 10.1175/JAS3465.1 952 960 , 2011. 10.1007/s10546-010-9522-z 10.1175/2008JAMC1675.1 10.1175/1520-0426(1998)015<0416:FSEFAA>2.0.CO;2 10.1007/s10546-011-9691-4 10.1023/A:1026002301152 in adoi: large basin under very stable conditions, Bound.-Lay. Meteorol., 137, 97–113, 14519–14526, doi: 2011 the research UAV “M to “Measuring the 3-D windMeas. vector Tech., with 4, a 1421–1444, weight-shift1515-2011 2011, microlight aircraft” Atmos. published Meas. in Tech., Atmos. 4, 1515–1539, doi: wet and dry planetary boundary2097, layers doi: coupled to the land surface, J. Atmos. Sci., 62,tracked 2078– with an automobiledoi: measurement system, J. Appl. Meteorol. Clim., 47, 2581–2599, air pooling in valleys, Bound.-Lay.2010. Meteorol., 134, 85–108, doi: meteorological observations, J.0426(1996)013<0921:AMMFFM>2.0.CO;2 Atmos. Ocean. Tech., 13,craft 921–936, for doi: boundary-layer research, J. Atmos. Ocean. Tech., 8, 19–40, doi: ibration and quality assuranceOcean. of Tech., flux 30, observations 161–181, from doi: a small research aircraft, J. Atmos. the wind vector using the1969–1982, autonomous doi: mini aerial vehicle M stationary generation of weak turbulenceLay. Meteorol., for 147, very 179–199, stable doi: and weak-wind conditions, Bound.- 0426(1991)008<0019:AOARAM>2.0.CO;2 doi: SUMO: a new perspectiveAtmos. Phys., for 116, the 15–26, doi: evaluation of fine-scale atmosphericof models, foehn Meteorol. 0426(2002)019<1545:AAPFTM>2.0.CO;2 and gap flows, J. Atmos. Ocean. Tech., 19, 1545–1556, doi: Brook, J. R.: Measurements ofClim., enhanced 51, turbulent 1618–1632, mixing doi: near highways, J. Appl. Meteorol. Atmos. Sci.,1986. 43, 1198–1209, doi: and other turbulence statistics?,0426(1994)011<0661:HLILEW>2.0.CO;2 J. Atmos. Ocean. Tech., 11, 661–673, doi: Society, Boston, MA, USA, 1986. erogeneity on low-leveldoi: horizontal wind speeds, Bound.-Lay. Meteorol., 143, 409–432, anemometer temperature to measure sensible heat5, flux 2095–2111, in doi: strong winds, Atmos. Meas. Tech., ground-based fluxmeasurements duringdoi: OASIS95, Bound.-Lay. Meteorol., 110, 39–67, Martínez, D., Jiménez, M., Cuxart, J., and Mahrt, L.: Heterogeneous nocturnal cooling Mann, J. and Lenschow, D. H.: Errors in airborne flux measurements, J. Geophys. Res., 99, Patton, E. G., Sullivan, P. P., and Moeng, C.-H.: The influence of idealized heterogeneity on Straka, J. M., Rasmussen, E. N., and Fredrickson, S. E.: A mobile mesonet for finescale Martin, S., Bange, J., and Beyrich, F.: Meteorological profiling of the lower troposphere using Raab, T. and Mayr, G.: Hydraulic interpretation of the footprints of SierraSmith, Nevada S., windstorms Brown, A., Vosper, S., Murkin, P., and Veal, A.: Observations and simulations of cold Vellinga, O. S., Dobosy, R. J., Dumas, E. J., Gioli, B., Elbers, J. A., and Hutjes, R. W. A.: Cal- Metzger, S., Junkermann, W., Butterbach-Bahl, K., Schmid, H. P., and Foken, T.: Corrigendum Tjernström, M., and Friehe, C. A.: Analysis of a radome air-motion system on a twin-jet air- van den Kroonenberg, A., Martin, T., Buschmann, M., Bange, J., and Vörsmann, P.: Measuring Mahrt, L., Thomas, C., Richardson, S., Seaman, N., Stau Mayer, S., Sandvik, A., Jonassen, M., and Reuder, J.: Atmospheric profiling with the UAS Mahrt, L.: Flux sampling errors for aircraft and towers, J. Atmos. Ocean. Tech., 15, 416–429, Mayr, G. J., Vergeiner, J., and Gohm, A.: An automobile platform for the measurement Lenschow, D. H. and Stankov, B. B.: Length scales in the convective boundary layer, J. Gordon, M., Staebler, R. M., Liggio, J., Makar, P., Li, S.-M., Wentzell, J., Lu, G., Lee, P., and Lenschow, D. H., Mann, J., and Kristensen, L.: How long is long enough when measuring fluxes Lenschow, D. H. (Ed.): Probing the Atmospheric Boundary Layer, American Meteorological Kang, S.-L., Lenschow, D., and Sullivan, P.: E Burns, S. P., Horst, T. W., Jacobsen, L., Blanken, P. D., and Monson, R. K.: Using sonic Isaac, P., Mcaneney, J., Leuning, R., and Hacker, J.: Comparison of aircraft and 5 5 30 25 20 15 30 10 25 20 15 10 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 1 − 5ms = car v 10.1175/1520- = car 1 1 u − − 950 0.6 ms 0.5 ms 955 , 2000. ) Wind 1 − , 2001. 951 , 1 1 950 − − ––––0.5 ms 0.4 ms 968 967 , 1997. 1 1 − − ◦ ◦ for the final wind are evaluated using v 0.1 ms 0.1 ms 10.1023/A:1018966204465 ) 0.5 and Ψ u v , Pitch, RollHeading ( u 0.8 w Position 2.5 m – – Parameter GPS-INS Sonic (@ 20 ms ). Accuracy of the GPS-INS and sonic, given by the manufacturers, and the derived 3 10.1175/1520-0426(2000)017<0795:WMOAMT>2.0.CO;2 doi: boprop aircraft accounting for flow distortion, J. Atmos. Ocean. Tech., 17, 795–810, and aircraft0426(1997)014<0512:QCAFSP>2.0.CO;2 data, J.Meteorol., 99, 127–150, doi: Atmos. Ocean. Tech., 14, 512–526, doi: Table 1. accuracy of the final wind. Williams, A. and Marcotte, D.: Wind measurements on a maneuvering twin-engine tur- (see Eq. Vickers, D. and Mahrt, L.: Quality control and flux sampling problems for tower Wilczak, J., Oncley, S., and Stage, S.: Sonic anemometer tilt correction algorithms, Bound.-Lay. 5 Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). 1 is the horizontal car speed (see Eq. | h INS V | ) Length of tracks (m) 1 970 969 − (ms | h INS V | 1 and 23 to 6 13.27 to 1415 to 15.9 20 21.2 26.8 780 900 900 900 Tracks Basic characteristics of the 20 car tracks. Photo of the instrumented car. Fig. 1. Table 2. Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

). 19 19 19 T 16 16 16 tower car 13 13 13 ), wind direction (dir), V 10 10 10 Track number Track number Track number 7 7 7 4 4 sonic tower sonic car TC tower TC car 4 tower car 1 1 1

3 2 1 0

50 −1

) v (m s (m v 291 290 289 350 300 250 200 150 100 292

T (K) T ) ( dir −1 °

972 971 ) wind components, and temperature ( 19 19 19 w 16 16 16 tower car 13 13 13 10 10 10 ) and vertical ( Track number Track number Track number v 7 7 7 4 4 4 tower car tower car 1 1 1

0 0 2 1 0 1

−1 0.1 2.5 1.5 0.5 1.5 0.5

)

V (m s (m V 0.05 −0.1 −0.5

), northward ( ) s (m u

−1 −0.05

19 19 19 19 19 19 19 19 is obtained from Eq. σ 16 16 16 16 16 16 16 16 13 13 13 13 13 13 13 13 10 10 10 10 10 10 10 10 , where σ sonic car TC tower TC car sonic tower Track number Track number Track number Track number Track number Track number Track number Track number 7 7 7 7 7 7 7 7 sonic tower sonic car TC tower TC car tower car sonic tower sonic car TC tower TC car tower car tower car 4 4 4 4 4 4 4 4 tower car sonic tower sonic car TC tower TC car 1.96 ± 1 1 1 1 1 1 1 1

1 0 3 2 1 0 2 0 0 3 2 1 0 2 1 0

1.5 0.5 0.3 0.2 0.1 2.5 1.5 0.5

0.2 0.1 2.5 1.5 0.5 1.5 0.5

) (K T ) s (m v ) s (m ) (K T

0.35 0.25 0.15 0.05 v 0.05

0.05 0.25 0.15 0.05

−0.1 −0.1

) s m (K T w ) s m (K T w

2 ′ 2 ′

2 2 − 2

2 − 2

−0.05 2

−0.05

) s (m w v ) s (m w v ′ ′ ′ ′

1 − 1 −

′ ′ ′ ′ 2 − 2 2 − 2

974 973 19 19 19 19 19 19 19 19 16 16 16 16 16 16 16 16 13 13 13 13 13 13 13 13 10 10 10 10 10 10 10 10 tower car Track number Track number Track number Track number Track number Track number Track number Track number 7 7 7 7 7 7 7 7 tower car tower car tower car tower car tower car tower car tower car 4 4 4 4 4 4 4 4 1 1 1 1 1 1 1 1

2 1 0 0 0 4 3 4 3 2 1 0 0 0

) s (m u ) s (m

0.2 0.2 0.1 u 0.1 0.4 0.2 0.1 0.1 0.4 0.2

2 ′ 2 ′

2 − 2 2 −

0.15 0.05 2 0.15 0.05

0.05 0.15 0.15 0.05

−0.1 −0.2 −0.4 −0.6 −0.8 −0.1 −0.2 −0.4 −0.6 −0.8

) s (m w ) s (m w ) s (m v u ) s (m v

−0.05 u −0.05

) s (m w u ) s (m w u 2 ′ 2 ′ ′ ′ ′ ′

2 − 2 2 − 2 2 − 2 2 − 2

′ ′ ′ ′ 2 − 2 2 − 2 , except that the averaging interval for the tower data is 2 min. 4 Car vs. tower for fluxes and variances. Averaging interval for the tower data is 10 min. As in Fig. Fig. 5. for both fluxes and variances). Fig. 4. The error bars represent the 95 % confidence intervals ( Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | ). The

2.2 1 1 1 1 10 10 0 0 −1 −1 10 10 ), yielding the four 2 10 10 ) ) 0 0 −1 −1 10 10 (m) (m) f (Hz) f (Hz) λ λ −1 −1 k (rad m k (rad m 10 10 100 100 Car speed = 15.9 m s Car speed = 26.8 m s −1 −1 10 10 −2 −2 10 10

1000 1000 −4 −6 −8 0 −2 −4 −6 −8 0 −2 −1 −2 −3 1 0 −1 −2 −3 1 0

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

−1 −1 −1 −1

v v T v

) s (m PSD ) s (m PSD

) K (m PSD ) s (m PSD

−1 2 −1 2 2 −1 2 Car wind INS INS roll −5/3 13.2 m s 15.9 m s 21.2 m s 26.8 m s Tower k 976 975 1 1 1 1 10 10 0 0 −1 −1 10 10 10 10 ) ) 0 0 −1 −1 10 10 (m) (m) λ λ f (Hz) f (Hz) −1 −1 k (rad m k (rad m 10 10 100 100 Car speed = 21.2 m s Car speed = 13.2 m s −1 −1 10 10 −2 −2 10 10 1000 1000 0 −1 −2 −3 0 −1 −2 −3 1 1 −2 −4 −6 −8 0 −2 −4 −6 −8 0

), while the tower spectra are averaged over all tracks.

10 10 10 10 10 10 10 10 10 10

w u

2 v

) s (m PSD ) s (m PSD

−2 3 −2 3 −1 2 −1 2 (recall that the GPS-INS and sonic coordinate systems are aligned; Sect. 1 Sonic wind components and temperature car vs. tower wavenumber spectra. The car Frequency spectra of the lateral component (in the car coordinate system) for the car − Fig. 7. sonic and the GPS-INSponent. motion, as The well latter as is the1.5 overestimated ms contribution as of the the product roll angle of to the the roll lateral angle com- and mean wind speed of Fig. 6. spectra are averaged over(see all Table tracks with the same car speed, yielding four groups of tracks spectra are averaged overpanels. all tracks with the same car speed (see Table Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

1 1 1 1 10 10 10 10 −1 −1 −1 −1 0 0 0 0 10 10 10 10 f (Hz) f (Hz) f (Hz) f (Hz) Car speed = 15.9 m s Car speed = 26.8 m s Car speed = 15.9 m s Car speed = 15.9 Car speed = 26.8 m s −1 −1 −1 −1 10 10 10 10

−4 −6 −8 0 −2 −4 −6 −8 0 −2 −4 −6 −8 0 −2 −4 −6 −8 0 −2

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

w w u u

) s (m PSD ) s (m PSD ) s (m PSD ) s (m PSD

−1 2 −1 2 −1 −1 2 2 Car wind INS INS pitch INS roll Car wind INS INS pitch 978 977 1 1 1 1 10 10 10 10 −1 −1 −1 −1 0 0 0 0 10 10 10 10 f (Hz) f (Hz) f (Hz) f (Hz) Car speed = 13.2 m s Car speed = 21.2 m s Car speed = 13.2 m s Car speed = 13.2 Car speed = 21.2 m s −1 −1 −1 −1 10 10 10 10 , except for the longitudinal component and the contribution of pitch to the , except for the vertical component and the contributions of both pitch and 7 7 0 −2 −4 −6 −8 0 −2 −4 −6 −8 0 −2 −4 −6 −8 0 −2 −4 −6 −8

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

w w u u

) s (m PSD ) s (m PSD ) s (m PSD ) s (m PSD

−1 2 −1 2 −1 2 −1 2 As in Fig. As in Fig. Fig. 9. roll to the vertical component. Fig. 8. longitudinal component.