uid=AND,o=lter,dc=ecoinformatics,dc=org all public read MV007 Christoph K Thomas

Professor, Micrometeorology; Associate Editor Water Resources Research; University of Bayreuth; Micrometeorology Group Bayreuth 95540 Germany

+49 (0) 921 55 2293 christoph.thomas@uni-bayreuth.de http://www.bayceer.uni-bayreuth.de/meteo Christoph K Thomas

Professor, Micrometeorology; Associate Editor Water Resources Research; University of Bayreuth; Micrometeorology Group Bayreuth 95540 Germany

+49 (0) 921 55 2293 christoph.thomas@uni-bayreuth.de http://www.bayceer.uni-bayreuth.de/meteo Principal Investigator Stephen Drake sdrake@coas.oregonstate.edu Other Researcher Laura Kingzett Other Researcher John McGinity Other Researcher Christoph K Thomas

Professor, Micrometeorology; Associate Editor Water Resources Research; University of Bayreuth; Micrometeorology Group Bayreuth 95540 Germany

+49 (0) 921 55 2293 christoph.thomas@uni-bayreuth.de http://www.bayceer.uni-bayreuth.de/meteo Creator 2017-06-29 This dataset was collected during one of the ARCFLO (Advanced Resolution Canopy FLOw) experiment series’ field campaigns. This field campaign was carried out in WS1 of the HJ Andrews Experimental forest during July-September 2012 by the biomicrometeorology group, PI Christoph Thomas. The ARCFLO experiment series spanned a wide range of topographic conditions (flat, sloped, mountainous) and canopy architectures (grassland, orchard, open forest, dense forest) and was carried out between 2011 and 2014. It was funded through the NSF Career Award in Physical and Dynamical Meteorology to PI Christoph Thomas. The main goal of this project was to develop a novel improved framework to describe the airflow and its transport under weak-wind conditions for a continuous variation of overstory density and stratification. The objective is to i) identify forcing mechanisms of submeso motions, ii) evaluate the impact of plant canopies of different overstory density on the wind, temperature, and humidity fields, and iii) improve predictors for mixing in plant canopies that incorporate the important physical mechanisms. Observations were be made with a unique combination of new and standard techniques including optical fiber measurement of temperature structure, acoustic remote sensing, ultrasonic anemometers, and laser-illuminated flow visualizations. microclimate wind direction wind speed LTER controlled vocabulary Related PublicationsDrake, Stephen; Kingzett, Laura; Mcginity, John ; Thomas, Christoph K. . 2012. ARCFLO 2012 Field Report. Corvallis, OR: Oregon State University; November 16, 2012 [unpublished, internal report], 105 p.Related FilesTitle: ARCFLO Station MapDescription: Detailed map, including UTMs and elevation of SUSAN stations within WS01URL: https://andrewsforest.oregonstate.edu/sites/default/files/lter/data/studies/mv007/arcflo_stations_map_detail.pdf Data Use Agreement: The re-use of scientific data has the potential to greatly increase communication, collaboration and synthesis within and among disciplines, and thus is fostered, supported and encouraged. This Data Set is released under the Creative Commons license CC BY "Attribution" (see: https://creativecommons.org/licenses/by/4.0/). Creative Commons license CC BY - Attribution is a license that allows others to distribute, remix, tweak, and build upon your work (even commercially), as long as you are credited for the original creation. This license accommodates maximum dissemination and use of licensed materials. It is considered professional conduct and an ethical obligation to acknowledge the work of other scientists. The Data User is asked to provide attribution of the original work if this data package is shared in whole or by individual parts or used in the derivation of other products. A recommended citation is provided for each Data Set in the Andrews LTER data catalog (see: http://andlter.forestry.oregonstate.edu/data/catalog/datacatalog.aspx). A generic citation is also provided for this Data Set on the website https://portal.edirepository.org in the summary metadata page. Data Users are thus strongly encouraged to consider consultation, collaboration and/or co-authorship with the Data Set Creator. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed and all data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. General acknowledgement: Data were provided by the HJ Andrews Experimental Forest research program, funded by the National Science Foundation's Long-Term Ecological Research Program (DEB 2025755), US Forest Service Pacific Northwest Research Station, and Oregon State University. http://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=MV007 WS01 of the HJ Andrews Experimental Forest -122.25773000 -122.24918000 44.20729000 44.20421000 2012-07-02 2012-09-17 Air exchange between forests and the lower atmosphere plays an important role for the transport of heat, moisture, momentum and other trace gases between the ground surface and the atmosphere, thereby directly impacting human life and the environment. Much remains to be learned about the mechanisms of the air exchange within the canopy layer, and its interaction with the deeper atmospheric boundary layer. The generally weak subcanopy winds and the mechanical barrier of the overstory render conceptual frameworks, such as commonly applied similarity theories, inadequate. The common generation of turbulence by shear on a variety of time scales, poor exchange between the subcanopy and above-canopy air, and short-circuiting of the energy cascade are not included in similarity theory that forms the basis for turbulent fluxes in models. Moreover, always-present background ‘submeso’ motions of spatial scales from tens of meters to several kilometers become important and lead to unpredictable sudden wind direction changes, intermittent mixing, and non-equilibrium turbulence. No current physical concept describes the nature of these motions. Cases of weak airflow in concert with limited vertical mixing also maintain high concentrations of contaminants near the surface, determined by poorly predicted within-canopy transport.

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Andrews Forest LTER Program US Forest Service Pacific Northwest Research Station 3200 SW Jefferson Way Corvallis OR 97331

hjaweb@fsl.orst.edu http://andrewsforest.oregonstate.edu/ Andrews Forest LTER Site

Forest Ecosystems and Society Department in Forestry Oregon State University 201K Richardson Hall Corvallis OR 97331-5752

(541) 737-8480 lterweb@fsl.orst.edu http://andrewsforest.oregonstate.edu/ Field Methods - MV007 Each subset of SUSAN (SUbcanopy Sonic ANemeometer) is comprised 4 Young 8100VRE UltraSonic Anemometers and 4 Vaisala HMP Thermohygrometers logging to a Campbell Scientific CR3000 Micrologger. Each of three SUSAN arrays is named by convention starting with a letter, ’A’, ’B’, or ’C’ and each subunit is numbered 1 through 4. All Vaisala HMP thermohygrometers are model 155 except for units C3 and C4 which are model 45C. All thermohygrometers are housed in an electrically aspirated radiation shield. For this experiment three SUSAN systems logged data at 20Hz and also logged data averaged at 1- minute intervals. Data was stored on 2-gigabyte SanDisk Extreme III flash cards by Campbell Scientific NL-155 Compact Flash Modules attached to each logger. Periodically, the flash card would be swapped so data could be uploaded from the flash card to a PC and then converted to ASCII format using the Campbell Scientific Card Convert program (a subunit of LoggerNet). Models/Algorithms - MV007 The sonic anemometer raw data (20 Hz) were processed post field collection using the Matlab based program BMMFLUX, written and developed by PI Christoph Thomas. During the processing, raw (20 Hz) data are checked according to instrument data quality flags and user-assigned plausibility thresholds: %% Plausibility limits for wind components (m/s) and sonic temperature (deg C) of raw signals: plaus_u = [-30,30]; plaus_v = [-30,30]; plaus_w = [-30,30]; plaus_T = [-30,50]. The observations from the thermohygrometers were not processed with BMMFLUX, but samples were aggregated into 1 min averages of air temperature and vapor pressure by the data logger. These logger-produced data were then combined with the 1-min averaged data output of BMMFLUX to yield the data described here. Note: In the variable label, ‘unrotated’ means recorded in the native sonic anemometers coordinate system (Ux, Uy, Uz as indicated in the manual). The label ‘rotated’ means that the winds were rotated into streamlines coordinate most suitable for micrometeorological purposes by performing two rotations (1: mean cross-wind equals zero m/s, 2: mean vertical motions equals zero m/s, for details see: Wilczak, J.M., Oncley, S.P., Stage, S.A., 2001. Sonic anemometer tilt correction algorithms. Boundary-Layer Meteorol. 99, 127–150.). Wind directions were also orrected for the instrument azimuth. The results are cylindrical coordinates commonly known as ‘wind speed’ and ‘wind direction’. The wind directions were not corrected for magnetic declination (With a latitude of 44.2 N and longitude of 122.2 W the declination was given by (http://www.ngdc.noaa.gov/geomagmodels/Declination.jsp) on 7/27/2012 is 15 degrees, 35 minutes = 15.583 degrees). Sampling frequency: 1 minute This dataset here contains only the observations from the network of ultrasonic anemometers and associated aspirated thermohygrometers consisting of 12 stations total grouped into 3 x 4 stations (SUSAN ABC, 1234). SUSAN stands for ‘SUbcanopy Sonic Anemometer Network’. Station locations for the WS1 ARCFLO experiment were selected to capture the greatest extent of spatial variability of the airflow. The first subset of stations (SUSAN A1,A2,A3,A4) were deployed near the flux tower near the mouth of the WS1, the second subset of stations (SUSAN B1,B2,B3,B4) were deployed about 200m upslope in the vicinity of the creek, and the third subset of stations (SUSAN C1,C2,C3,C4) in close proximity to the confluence of the two smaller creeks in the upper part of WS1 approx. 1 km upstream. With the exceptions of SUSAN A2, which was mounted on WS1 tower and SUSANs C1 and C2, which were mounted on a temporary 40ft tower, all SUSAN subunits were mounted on adjustable tripods to facilitate sonic leveling. SUSANs A and B were powered by line power whereas SUSAN C was powered by four AGM 12-volt batteries. These batteries were recharged every 4 to 6 days with a portable generator. Sonics were connected to loggers with 300 ft of AGU 24 communications cable. Data was transmitted to the Campbell Sci. Cr3000 data loggers through RS-485 protocol and translated to RS-422 by CommFront 485-422 TTL converters contained within the logger weatherproof box. With this deployment configuration we aimed to capture individual submeso features as they propagated up or down the watershed past various sensors (see deployment map). Andrews Experimental Forest (HJA) -122.26172200 -122.10084700 44.28196400 44.19770400 1631 1631 meter Andrews Watershed 1 -122.25683100 -122.23581300 44.20851700 44.19901700 1027 1027 meter Subcanopy Sonic Anemometer Network (SUSAN) A1 -122.25671000 -122.25671000 44.20648000 44.20648000 518 518 meter Subcanopy Sonic Anemometer Network (SUSAN) A2 -122.25729000 -122.25729000 44.20680000 44.20680000 495 495 meter Subcanopy Sonic Anemometer Network (SUSAN) A3 -122.25773000 -122.25773000 44.20705000 44.20705000 450 450 meter Subcanopy Sonic Anemometer Network (SUSAN) A4 -122.25656000 -122.25656000 44.20729000 44.20729000 511 511 meter Subcanopy Sonic Anemometer Network (SUSAN) B1 -122.25486000 -122.25486000 44.20610000 44.20610000 381 381 meter Subcanopy Sonic Anemometer Network (SUSAN) B2 -122.25457000 -122.25457000 44.20586000 44.20586000 513 513 meter Subcanopy Sonic Anemometer Network (SUSAN) B3 -122.25493000 -122.25493000 44.20588000 44.20588000 509 509 meter Subcanopy Sonic Anemometer Network (SUSAN) B4 -122.25488000 -122.25488000 44.20595000 44.20595000 508 508 meter Subcanopy Sonic Anemometer Network (SUSAN) C1 -122.25055000 -122.25055000 44.20508000 44.20508000 588 588 meter Subcanopy Sonic Anemometer Network (SUSAN) C2 -122.25055000 -122.25055000 44.20508000 44.20508000 588 588 meter Subcanopy Sonic Anemometer Network (SUSAN) C3 -122.24918000 -122.24918000 44.20448000 44.20448000 593 593 meter Subcanopy Sonic Anemometer Network (SUSAN) C4 -122.24937000 -122.24937000 44.20421000 44.20421000 578 578 meter Subcanopy Sonic Anemometer Network (SUSAN) ARCFLO sampling sites -122.25773000 -122.24918000 44.20729000 44.20421000 593 593 meter Sherri L. Johnson

US Forest Service ;Pacific NW Research Station ;3200 SW Jefferson Way Corvallis OR 97331 USA

541-758-7771 sherri.johnson2@usda.gov sherri.johnson@oregonstate.edu https://www.fs.fed.us/research/people/profile.php?alias=sherrijohnson Principal Investigator Julia A. Jones

Oregon State University;Department of Geosciences; Wilkinson Hall 104 Corvallis OR 97331-5506 USA

(541) 737-1224 Julia.Jones@oregonstate.edu geojulia@comcast.net http://ceoas.oregonstate.edu/profile/jones/ http://orcid.org/0000-0001-9429-8925 Principal Investigator Matthew G Betts

Department of Forest Ecosystems and Society; 201E Richardson Hall; College of Forestry; Oregon State University Corvallis OR 97331

(541) 737-3841 matt.betts@oregonstate.edu http://www.fsl.orst.edu/flel/index.htm Principal Investigator Michael P. Nelson

Department of Forest Ecosystems and Society; 201K Richarson Hall; College of Forestry; Oregon State University Corvallis OR 97331

541-737-9221 mpnelson@oregonstate.edu http://www.michaelpnelson.com http://orcid.org/0000-0001-6917-4752 Principal Investigator David Bell david.bell@usda.gov david.bell@oregonstate.edu https://lemma.forestry.oregonstate.edu/about/david-bell Principal Investigator The H.J. Andrews Experimental Forest is a living laboratory that provides unparalleled opportunities for the study of forest and stream ecosystems in the central Cascade Range of Oregon. Since 1980, as a part of the National Science Foundation Long Term Ecological Research (NSF-LTER) program, the Andrews Experimental Forest has become a leader in the analysis of forest and stream ecosystem dynamics. Long-term field experiments and measurement programs have focused on climate dynamics, streamflow, water quality, and vegetation succession. Currently researchers are working to develop concepts and tools needed to predict effects of natural disturbance, land use, and climate change on ecosystem structure, function, and species composition. The Andrews Experimental Forest is administered cooperatively by the USDA Forest Service Pacific Northwest Research Station, Oregon State University and the Willamette National Forest. Funding for the research program comes from the National Science Foundation (NSF), US Forest Service Pacific Northwest Research Station, Oregon State University, and other sources. Data were provided by the HJ Andrews Experimental Forest research program, funded by the National Science Foundation's Long-Term Ecological Research Program (DEB 2025755), US Forest Service Pacific Northwest Research Station, and Oregon State University. National Science Foundation: DEB1440409 The Andrews Forest is situated in the western Cascade Range of Oregon, and covers the entire 15,800-acre (6400-ha) drainage basin of Lookout Creek. Elevation ranges from 1350 to 5340 feet (410 to 1630 m). Broadly representative of the rugged mountainous landscape of the Pacific Northwest, the Andrews Forest contains excellent examples of the region's conifer forests and associated wildlife and stream ecosystems. These forests are among the tallest and most productive in the world, with tree heights of often greater than 250 ft (75 m). Streams are steep, cold and clean, providing habitat for numerous aquatic organisms. 1 MV00701 Subcanopy Sonic Anemometer Network (SUSAN): MV00701.txt 0 ebca1e40c1b07eba813276e1c85d6dee 1 \r\n column , " http://andlter.forestry.oregonstate.edu/ltermeta/ltersearch/dataaccess.aspx?docid=MV00701_v1.txt 2012-07-02 2012-09-17 DBCODE FSDB Database Code char(5) MV007 FSDB Database Code MV007 ENTITY Entity Number numeric(2,0) number 1 natural 1.0000 1.0000 STATION SUSAN Station Number char(8) SUSAN_A1 Subcanopy Sonic Anemometer Network (SUSAN) A1 SUSAN_A2 Subcanopy Sonic Anemometer Network (SUSAN) A2 SUSAN_A3 Subcanopy Sonic Anemometer Network (SUSAN) A3 SUSAN_A4 Subcanopy Sonic Anemometer Network (SUSAN) A4 SUSAN_B1 Subcanopy Sonic Anemometer Network (SUSAN) B1 SUSAN_B2 Subcanopy Sonic Anemometer Network (SUSAN) B2 SUSAN_B3 Subcanopy Sonic Anemometer Network (SUSAN) B3 SUSAN_B4 Subcanopy Sonic Anemometer Network (SUSAN) B4 SUSAN_C1 Subcanopy Sonic Anemometer Network (SUSAN) C1 SUSAN_C2 Subcanopy Sonic Anemometer Network (SUSAN) C2 SUSAN_C3 Subcanopy Sonic Anemometer Network (SUSAN) C3 SUSAN_C4 Subcanopy Sonic Anemometer Network (SUSAN) C4 DATETIME Date and time in Pacific Standard Time (PST) of sensor reading datetime YYYY-MM-DD hh:mm:ss 7/2/2010 12:20:00 PM 9/17/2012 2:06:00 PM U_MEAN_ROT mean horizontal wind speed numeric(5,2) meters per second 1 real 0.0000 3.5000 PHI_MEAN mean horizontal wind direction numeric(3,0) degrees azimuth 1 whole 0.0000 360.0000 W_MEAN_UNROT mean vertical wind speed, unrotated numeric(5,2) meters per second 1 real -1.6700 1.1400 W_STD_ROT standard deviation of the vertical wind speed, rotated numeric(4,2) meters per second 1 real 0.0000 1.0000 TS_MEAN mean sonic air temperature numeric(5,2) degrees Celsius 1 real 4.2600 39.6700 T_HMP mean dry-bulb air temperature numeric(5,2) degrees Celsius 1 real 2.8700 38.8100 E_HMP mean air vapor pressure numeric(5,3) kilopascal 1 real 0.5130 2.6950 PRIMARY MV00701.STATION MV00701.DATETIME NOTNULL MV00701.DBCODE MV00701.ENTITY MV00701.STATION MV00701.DATETIME 1280756 dimensionless number, i.e., ratio, count degrees azimuth (0-360) meters per second Degrees Celsius; a common unit of temperature; constantToSI=273.18 kilopascal