2008-2014 Soil temperature, thermal conductivity, water content, CO2, and pressure at the Manitou Experimental Forest, Colorado during the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen (BEACHON) study

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Frank, John M.
Originator: Massman, William J.
Publication_Date: 2020
Title:
2008-2014 Soil temperature, thermal conductivity, water content, CO2, and pressure at the Manitou Experimental Forest, Colorado during the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen (BEACHON) study
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2020-0061
Description:
Abstract:
This data publication contains continuous soil measurements from the Manitou Experimental Forest, Colorado taken from December 2008 through August 2014. Data files contain soil temperature and water content summarized every 5-minutes and 30-minutes; soil thermal conductivity and carbon dioxide (CO2) summarized every 30-minutes; and soil air pressure summarized every 1-second, 5-minutes, and 30-minutes. Raw data are also provided for the 5-minute soil temperature, water content, and pressure measurements plus 1-Hz temperature and heating curves used to calculate thermal conductivity.
Purpose:
The two principal objectives to this study were to (1) obtain quantitative estimates of the influence that (i) atmospheric pressure pumping and (ii) thermal expansion and contraction of the air in the pore spaces of soil can have in the transport (and fluxes) of trace gases in soils and (2) obtain estimates of surface heat flux for energy balance studies in support of NCAR’s BEACHON project.

From 2008 to 2013, the National Center for Atmospheric Research (NCAR) led the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen (BEACHON) study at the Manitou Experimental Forest, Colorado. The purpose of this study was to investigate the physical relationships between biogenic emissions and aerosols, hydrology and cloud formations, and carbon assimilation within water limited ecosystems. As part of this study, the USDA Forest Service investigated the role of soils, and focused on soil temperature, thermal conductivity, water content, CO2, and pressure.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20081218
Ending_Date: 20140814
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As Needed
Spatial_Domain:
Description_of_Geographic_Extent:
The Manitou Experimental Forest (MEF) is located 28 miles northwest of Colorado Springs, Colorado, and covers about 17,000 acres in the South Platte River drainage. The Forest is representative of the montane ponderosa pine zone in the Front Range which extends from southern Wyoming to northern New Mexico. Elevation ranges from about 7,500 to 9,300 feet. The BEACHON soil study was located 1.2 kilometers (km) west (280° from north) of the MEF headquarters in a small 0.2 hectare opening of the forest.
Bounding_Coordinates:
West_Bounding_Coordinate: -105.107433
East_Bounding_Coordinate: -105.106833
North_Bounding_Coordinate: 39.102567
South_Bounding_Coordinate: 39.102033
Bounding_Altitudes:
Altitude_Minimum: 2392
Altitude_Maximum: 2389
Altitude_Distance_Units: meters above sea leavel
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: geoscientificInformation
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Ecology, Ecosystems, & Environment
Theme_Keyword: Soil
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: BEACHON
Theme_Keyword: pressure pumping
Theme_Keyword: soil CO2
Theme_Keyword: soil carbon dioxide
Theme_Keyword: soil pressure
Theme_Keyword: soil temperature
Theme_Keyword: soil thermal conductivity
Theme_Keyword: soil water content
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Manitou Experimental Forest
Place_Keyword: Colorado
Place_Keyword: South Platte River
Place_Keyword: Colorado Springs
Access_Constraints: None
Use_Constraints:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Frank, John M.; Massman, William J. 2020. 2008-2014 Soil temperature, thermal conductivity, water content, CO2, and pressure at the Manitou Experimental Forest, Colorado during the Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics & Nitrogen (BEACHON) study. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2020-0061
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: John Frank
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Position: Electronics Engineer
Contact_Address:
Address_Type: mailing and physical
Address: 240 W. Prospect Rd.
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: 970-498-1319
Contact_Electronic_Mail_Address: john.frank@usda.gov
Data_Set_Credit:
This study was funded by the USDA Forest Service, Rocky Mountain Research Station.
Cross_Reference:
Citation_Information:
Originator: Ortega, J.
Originator: Turnipseed, A.
Originator: Guenther, A.B.
Originator: Karl, T.G.
Originator: Day, D.A.
Originator: Gochis, D.
Originator: Huffman, J.A.
Originator: Prenni, A.J.
Originator: Levin, E.J.T.
Originator: Kreidenweis, S.M.
Originator: DeMott, P.J.
Originator: Tobo, Y.
Originator: Patton, E.G.
Originator: Hodzic, A.
Originator: Cui, Y.Y.
Originator: Harley, P.C.
Originator: Hornbrook, R.S.
Originator: Apel, E.C.
Originator: Monson, R.K.
Originator: Eller, A.S.D.
Originator: Greenberg, J.P.
Originator: Barth, M.C.
Originator: Campuzano-Jost, P.
Originator: Palm, B.B.
Originator: Jimenez, J.L.
Originator: Aiken, A.C.
Originator: Dubey, M.K.
Originator: Geron, C.
Originator: Offenberg, J.
Originator: Ryan, M.G.
Originator: Fornwalt, P.J.
Originator: Pryor, S.C.
Originator: Keutsch, F.N.
Originator: DiGangi, J.P.
Originator: Chan, A.W.H.
Originator: Goldstein, A.H.
Originator: Wolfe, G.M.
Originator: Kim, S.
Originator: Kaser, L.
Originator: Schnitzhofer, R.
Originator: Hansel, A.
Originator: Cantrell, C.A.
Originator: Mauldin, R.L.
Originator: Smith, J.N.
Publication_Date: 2014
Title:
Overview of the Manitou Experimental Forest Observatory: site description and selected science results from 2008 to 2013
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Atmospheric Chemistry and Physics
Issue_Identification: 14(12): 6345-6367
Online_Linkage: https://www.fs.usda.gov/treesearch/pubs/46430
Online_Linkage: https://doi.org/10.5194/acp-14-6345-2014
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
The accuracy for each sensor type is described below.

For soil temperature, data were removed based on obvious outliers in their 5-minute averages or standard deviations, or obvious errors in the data logging system. Next, thermocouple errors associated with spurious panel voltage errors were corrected in multiple steps. First, data from 50 centimeters (cm) and 100 cm depths were LOESS filtered with a 4-day window; the residual noise between the raw signal and the LOESS filtered temperature were assumed to be panel voltage noise. Second, the noise estimated from these eight deep-sensors were weighted and averaged to estimate the noise of the other sensors based on their physical location on the multiplexer wiring; this estimated noise was removed from each sensor except those in replicate 1 between 0-7.5 cm depths, which could not be corrected. Finally, the panel-noise corrected data were LOESS filtered to remove the remaining noise by using individual window sizes that maximized noise removal while minimizing distorting natural transients in the data. The window lengths were 0.5 hours for the 0-0.5 cm depths, 1 hour for the 1.5-2.5 cm depths, and 2 hours for the 3.5-25 cm depths (exceptions were 0.5 hours at replicate 2 at 1.5 cm depth; 0.75 hours at replicate 1 at 1.5 cm depth, replicate 2 at 2.5 cm depth, replicate 4 at 0.5-1.5 cm depth; 1.25 hours at replicate 1 at 2.5 cm depth, replicates 2-3 at 3.5 cm depth; and 1.5 hours at replicate 4 at 3.5 cm depth). Based on these steps, all thermocouple measurements are probably within 0.2 degrees Celsius (C) accuracy with less noise for deeper sensors.

For thermal conductivity, measurements were conducted each half-hour, during which raw 1-hertz (Hz) soil temperature and were statistically fit to heating and cooling curves that predicted the increase temperature during heating as DeltaT = (q/(4*pi*lambda_h))*ln(t + tc) + d and during cooling as DeltaT = (q/(4*pi*lambda_c))*(ln(t + tc)-ln(t + tc - t0)) + d where the dependent variable is temperature increase, i.e., DeltaT, and the independent variables are the heat liberated per unit length of heater, i.e. q, and time, i.e. t; the model fitting parameters are thermal conductivity, i.e. lambda_h and lambda_c, and offsets for time and temperature, i.e. tc and d (note, t0 is a fixed offset of 60 seconds). This methodology is described in Bristow (2002). The thermal conductivity values were then inspected for obvious outliers in lambda_h, lambda_c, tc, d, and the difference between lambda_h and lambda_c, as well as obvious errors in the data logging system. Several sensors had heater failure during the study, which resulted in the removal of the thermal conductivity data, though not necessarily the initial temperature data.

For soil water content, a custom equation was used to convert the time domain reflectometry (TDR) measured soil apparent dielectric constant, Ka, to water content such that WC = -0.15119 + 0.057006*Ka - 0.0030539*Ka² + 0.00006601*Ka³. This calibration was derived in a previous study (Frank and Massman 2007) using TDR probes with soil from the Manitou Experimental Forest, and is based on the TDR calibration approach of Topp et al. (1980). Data were removed based on obvious outliers in their 5-minute values or obvious errors in the data logging system. Next, the data were LOESS filtered to remove noise by using individual window sizes that maximized noise removal while minimizing distorting natural transients in the data. The window lengths were 1.5 hours for the 2 cm depth, 2 hours for the 5 cm depth, 6 hours for the 10 cm depth, 12 hours for the 15 cm depths, 9 hours for the 20 cm depths, and 4 days for the 50-100 cm depths (exceptions were 1.25 hours at replicate 3 at 2 cm depth, 1.75 hours at replicate 3 at 5 cm depth, 2 hours at replicate 2 at 2 cm depth, 3 hours at replicate 2 at 5 cm depth, 4 hours at replicate 3 at 10-15 cm depths, and 9 hours at replicate 4 at 10 cm depth). Based on these steps as well as the results from the calibration of TDR probes using Manitou Experimental Forest soil, the accuracy of TDR water-content measurements was within 0.02 meters³/meters³ (m³/m³) with less noise for deeper sensors.

For soil CO2, data were removed based on obvious outliers in their 20-second averages or standard deviations, the amount of time or volume of air purged from each line, or obvious errors in the data logging system. Next, the CO2 data were calibration adjusted for in situ calibrations conducted intermittently during the field study. During typical site visits the CO2 analyzer was challenged with gases of 0, 390, and 8020 micromoles/mole (μmol/mol) concentrations of CO2. In circumstances when the calibration of the CO2 analyzer had drifted substantially, then the settings of the instrument were updated with these gases, and then a post-calibration set of measurements were recorded. In post processing, calibration adjustments were applied the CO2 analyzer based on the in situ pre and post calibration records comparing the 0, 390, and 8020 tanks to the values that the analyzer had reported. For each calibration exercise, the adjustment was calculated by fitting the dependent variable (CO2 analyzer output) to the independent variable (CO2 tank value) using a 2nd order polynomial. Due to the large range between 390 and 8020 μmol/mol (micromole), both the independent variables were log-transformed. The 2nd order polynomial was inverted using the quadratic equation, thus allowing the CO2 analyzer output to be corrected based on the CO2 tank values. During the time in between calibration records the 2nd order polynomial coefficients were linearly interpolated. Overall there were 46 valid calibrations during the study, with the longest gaps between checks from 3 September 2009 to 17 December 2009 (105 days), 17 December 2009 to April 7, 2010 (110 days), 13 September 2012 to 19 April 2013 (218 days), and 26 September 2013 to 10 April 2014 (196 days); all other gaps between calibrations were less than 100 days. Next, the data were corrected for spurious shifts in offset. Using the assumption that 0 cm depth measurements should tend to correspond to ambient CO2 values (i.e., ~ 400 μmol/mol), the surface CO2 data were filtered by computing the 24-hour running 10% quantile of the combined data from all four replicates (i.e., similar to a running mean or running minimum) which was subsequently LOESS filtered with a 4-day window. Concurrently, the ambient CO2 data from the GLEES AmeriFlux site 159 km north-northwest (Frank et al. 2018) was also filtered using a 24-hour running minimum which was subsequently LOESS filtered with a 4-day window. The shifts in offset were corrected by removing the LOESS-filtered 10%-quantile from the BEACHON soil CO2 data and replacing it with the LOESS filtered-minimum of the GLEES ambient CO2 data. Finally, the data were corrected for a few situations where the instrument response obviously shifted, yet the in situ calibration checks could not adequately capture or correct the error. Often this occurred when the CO2 instrument had drifted or was malfunctioning upon arrival and good calibration values could only be obtained after the equipment had been serviced or repaired. In these cases, it was assumed that the span of the calibration should be adjusted so that the data, especially at the deeper depths, matched up before and after the service or repair. This occurred on 8 July 2009, 26 August 2010, 12 May 2011, 9 June 2011, 1 September 2011, 21 October 2011, 17 November 2011, 13 July 2012, and 10 July 2013. Based on these steps, the soil CO2 data should be within the manufacturer's published accuracy of 6% for the LI-820. Though the LI-820 range was 0 to 20,000 umol/mol, the maximum calibration gas concentration used was 8,020 umol/mol; CO2 values above this were considered valid, though less accurate. At times the instrument’s sensitivity had decreased such that when post-hoc calibration corrections were applied the effective range was greater than 20,000 umol/mol; in a few circumstances the estimated CO2 concentration deep within the soil profile exceeded 20,000 umol/mol by ~10%.

For soil pressure, data were removed based on obvious outliers in their 5-minute averages or standard deviations. The data were corrected for the arbitrary pressure in the reference cell (see methodology description below for more details) by matching the 5-minute averages to the ambient pressure at the NCAR Manitou Experimental Forest Observatory from 8 July 2009 until 28 September 2012 (https://data.eol.ucar.edu/cgi-bin/codiac/fgr_form/id=496.003; these data provided by NCAR/EOL under the sponsorship of the National Science Foundation: https://data.eol.ucar.edu/) or afterward to an adjusted version of the ambient pressure at the Niwot Ridge AmeriFlux site 110 km north-northwest (https://ameriflux.lbl.gov/sites/siteinfo/US-NR1; Blanken et al. 1998); the Niwot Ridge data were LOESS filtered with a 2-day window and used as an independent variable to predict the NCAR pressure data from the equation P_NCAR = a*P_Niwot + b + c*sin(2*pi*t/365.25 + d) where a, b, c, and d are empirical fitting parameters and t is an independent variable for time in days. For both the NCAR and adjusted Niwot Data, the mean value of 76.283 kilopascal (kPa) at Manitou was removed from the datasets. The soil pressure data were also corrected for the temperature effect of the pressure within the reference cell; direct measurements of cell temperature were used, and if missing, the soil temperature at 50 cm depth as described above was substituted. A Bayesian statistical analysis predicted the corrected soil pressure as Ps = Ps_raw - P_initial + Density*Tcell*287.058*densityAdj - a*t - b*t² - c*t³, where the P_initial, densityAdj, a, b, and c are empirical fitting parameters with posterior probability distributions. Density is calculated from the NCAR/adjusted Niwot Ridge air pressure and cell temperature, and time is in minutes. The Bayesian analysis estimates the most likely combination of initial reference cell pressure, temperature drift, and time drift between every purging of the reference cell in order for each replicate soil pressure sensor to match the NCAR/adjusted Niwot Ridge air pressure. The Bayesian parameters were adjusted such that the analysis tried to match the four soil pressure sensors with the same precision to each other as to the NCAR air pressure, but it allowed the matching to the adjusted Niwot Ridge air pressure to be less rigorous considering this dataset was a surrogate for the actual pressures at Manitou. Finally, the combined offset of -P_initial + Density*Tcell*287.058*densityAdj - a*t - b*t² - c*t³ was calculated for each five-minute period, and then interpolated to 1 Hz and added to the raw pressure data. Based upon this methodology, which treats the NCAR air pressure sensor as a standard, the average accuracy of the soil pressure sensors is 17 pascals (Pa) while the standard deviation between the four soil pressure sensors was 1 Pa. Therefore, soil air pressure gradients can typically be measured within 1 Pa, though more accurate results can be obtained by forcing long-term trends at the various depths to be equal, though this is beyond the scope of this data archive.


References

Blanken, Peter D.; Monson, Russel K.; Burns, Sean P.; Bowling, David R.; Turnispeed, Andrew A. 1998. AmeriFlux US-NR1 Niwot Ridge Forest (LTER NWT1), Dataset. https://doi.org/10.17190/AMF/1246088

Bristow, Keith L. 2002. Thermal Conductivity. In: Dane, Jacob H.; Topp, Clarke G. (editors). 2002. Methods of Soil Analysis: Part 4. Physical Methods, Soil Science Society of America, Inc. Madison, WI, USA, pages 1209-1226.

Frank, John M.; Massman, William J. 2007. Effects of fuels reduction treatments on the soil temperature, heat-flux, water content, and CO2 at Manitou Experimental Forest. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RDS-2007-0002

Frank, John M.; Massman, William J.; Ewers, Brent E.; Williams, David G. 2018. Data and source code for "Bayesian analyses of seventeen winters of water vapor fluxes show bark beetles reduce sublimation". Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2018-0032

Topp, G.C.; Davis, J.L; Annan, A.P. 1980. Electromagnetic determination of soil water content: Measurements in coaxial transmission lines. Water Resources Research 16(3): 574-582. https://doi.org/10.1029/wr016i003p00574

UCAR/NCAR - Earth Observing Laboratory. 2012. BEACHON 5 minute ISFS data, not tilt corrected. Version 1.0. UCAR/NCAR - Earth Observing Laboratory. https://doi.org/10.5065/D6F769XG
Logical_Consistency_Report:
Quality assurance/quality control (QA/QC) checks and corrections generally involved removing data based on obvious outliers in their averages, standard deviations, or other ancillary diagnostics or obvious errors in the data logging system. For more specific details refer to the attribute accuracy report above.
Completeness_Report:
Gaps in the dataset for individual measurements are due to a sensor or instrument being offline (e.g., CO2 analyzer removed for repairs), a malfunction, or unrealistic values (e.g., snow on the surface pressure sensor). Gaps in all measurements indicate periods where the entire measurement system was not operating correctly (e.g., datalogger failure due to power outage). Depending on the time resolution of the data files, they contain records every 1 second, 5 minutes, or 30 minutes for the entire period of measurement. The exceptions are the raw thermal conductivity files, where 1 second data are reported only during the 2-minutes of each half-hour when the sensors were actively being measured.

Missing data are denoted as “.”.

In the 30-minute processed data, values of 1 and 0 are used to represent “True”/“False” regarding whether or not soil thermal conductivity was measured at each replicate at 0 millimeter depth.
Lineage:
Methodology:
Methodology_Type: Field
Methodolgy_Identifier:
Methodolgy_Keyword_Thesaurus:
None
Methodology_Keyword: thermocouple
Methodology_Keyword: time domain reflectometry (TDR)
Methodology_Keyword: thermal conductivity single probe heat pulse (SPHP) method
Methodology_Keyword: infrared gas analyzer (IRGA)
Methodology_Keyword: differential capacitance manometer
Methodology_Description:
STUDY LOCATION

The study was conducted on a gentle east facing slope with all sensors confined to a 15 m x 15 m plot that was mostly open from the forested canopy, 1.2 km west of the Manitou Experimental Forest headquarters. At the center of the plot was an elevated structure with control boxes, dataloggers, solar panels, and batteries. Replicate soil pits were located in four directions (rep 1 = northwest, rep 2 = northeast, rep 3 = southeast, rep 4 = southwest) about 4 m from the center. Each replicate had three pits, one for temperature and thermal conductivity probes that was ~1.3 m deep, one for soil moisture probes that was ~1 m deep, and one for soil CO2 probes that was ~1 m deep. A final pit was dug for soil pressure sensors ~9 m east of the plot center that was ~1 m deep and large enough to hold a 0.5 m x 0.5 m sensor/control box.


DATA COLLECTION

Temperature, thermal conductivity, and moisture sensors (replicates 1 and 2 only) were installed from 20-26 November 2008 (day 325-331). Data logging began on 18 December 2008 (day 353). CO2 pits and sensors were installed on 14 May 2009 (day 134) with replicate 3 connected on 8 July 2009 (day 189) and replicate 4 connected on 6 August 2009 (day 216). Soil moisture pits for replicates 3 and 4 were dug and sensors installed on 3 September 2009 (day 246). The pressure sensors were installed on 9 June 2011 (day 160) with data being logged on 20 July 2011 (day 201) and the pit being backfilled on 1 September 2011 (day 244). There were prominent gopher holes near the replicate 2 pits that were noted on 18 November 2009 (day 322) and again on 5 May 2010 (day 125), including possible disruption of the soil temperature sensor at 1.5 cm depth with disruption first noted on 1 October 2009 (day 275). All sensors were removed on 14 August 2014.

Soil temperature was measured in each replicate at 0, 0.5, 1.5, 2.5, 3.5, 7.5, 12.5, 17.5, 25, 75, and 125 cm depth. Temperatures were measured with type T thermocouples (PVC insulated, Omega Engineering, Sanford, CT) that were welded and covered with epoxy (Omegabond 101, Omega Engineering). Sensors were measured and recorded with a 23X datalogger (Campbell Scientific, Logan, UT) via an AM25T multiplexer. Measurements were made every 1 minute (min) and averages and standard deviations were recorded every 5 min.

Soil thermal conductivity was measured in each replicate at 0, 1, 2, 3, 5, 10, 15, 20, 50, and 100 cm depth. Sensors were constructed by East 30 Sensors (Pullman, WA) with 6 cm stainless steel needles (except 0 cm sensors which were 15 cm length) containing a heater wire and a type E thermocouple. Sensors were measured and recorded with a 23X datalogger via an AM25T multiplexer which was programmed to turn on the heater for 1 min, and recording the temperature for 2 min (i.e., 1 min of heating and 1 min of cooling). The procedure was repeated half-hourly. The heater voltage was adjusted to ~ 6 V and a precision resistor of ~1 ohm was wired in series with the heater water with the voltage across it measured on an AM25T multiplexer; the heater wire had a fixed resistance of 1041.5 ohms/m allowing for a calculation of the heat liberated per unit length of the needle in watts per minute (W/m). During installation the sensor at replicate 3 at 50 cm was noted as having poor contact with the surface. During the study many of the heaters burned out. The 0 cm, i.e., surface, sensors were only turned on briefly on 23 September 2011 (day 266) and then from 10 April 2014 (day 100) to the end of the study.

Soil water content was measured in each replicate at 2, 5, 10, 15, 20, 50, and 100 cm depth. Soil water content was measured using time-domain reflectometry, TDR, with a TDR100 and SDMX50SP multiplexer (Campbell Scientific) and measurements were initialized and recorded with a 23X datalogger every five minutes. CS610 TDR probes (Campbell Scientific) were used for all measurements. Sensors at 50 cm depth were noted as difficult to install due to a very hard soil layer.

Soil CO2 was measured in each replicate at 0, 2, 5, 10, 15, 20, 50, and 100 cm depth. Soil CO2 was measured in each location by pulling a sample from a hollow, permeable disk (1.1 cm thick by 5.1 cm radius) buried in the soil, through tubing (0.95 cm O.D., 0.64 cm I.D., Dekoron, Saint-Gobain Plastics) to a control box located at the plot center, through a solenoid manifold (Skinner valve, model 71215SN2MN00N0, Parker, New Britain, CT), through a filter (Balston, Haverhill, MA), a small cylinder with magnesium perchlorate desiccant, and through a pump (MPU 1046-N815, KNF Neuberger, Trenton, NJ) at approximately 2 liters per minute (LPM). A mass flow controller was used to set the flow rate to 2 LPM until it began to fail on 25 February 2012; the flow rate was subsequently set at 1 LPM until the controller was replaced on 13 July 2012. Afterwards, a mass flow sensor was used to measure the flow with the pump controlled only by a needle valve, which allowed for less precise control of the flow; flow rates were between 3-5 LPM. A 23X datalogging system was programmed to initially pull ~0.2 L of air from each tube, which was increased to ~0.33 L on 3 September 2009 (day 246), ~0.35 L on 26 August 2010 (day 238), ~0.38 L on 21 October 2010 (day 294), and finally decreased back to ~0.33 L on 24 August 2012 (day 237). A small amount of gas was diverted between the filter and the pump; it was pulled through an infrared gas-analyzer (LI-820, Li-Cor, Lincoln, NE) and a pump (MPU 1185 NMP08, KNF Neuberger) at approximately 0.5 LPM. Note, all other tubing was 0.64 cm O.D., 0.32 cm I.D., Bev-A-Line (Thermoplastic Processes, Stirling, NJ). Data were collected on a 23X datalogger, which monitored the CO2 concentration, flow rate, and calculated the amount of volume purged from the tube every 0.5 seconds. Once the desired volume was purged the datalogger shut off the flow and monitored the CO2 concentration at 2 hertz (Hz) for 20 seconds, and recorded the mean and standard deviation of the CO2. Three tanks of calibration gas (zero air; 390 umol/mol; 8,020 umol/mol CO2 in air, Scott Specialty Gas, Plumsteadville, PA) were intermittently used to calibrate the system during site visits; more detail on the calibration is provided in the attribute accuracy report above.

Soil pressure was measured in a separate location in one pit with inlets at 0, 10, 20, and 50 cm. Each inlet used a stainless steel fitting (Swagelok, Solon, OH) with one end covered with porous stainless steel mesh but otherwise open to the soil and the other end connected to Dekoron tubing (.95 cm O.D., 0.64 cm I.D). The tubing was buried ~0.5 m deep and each tube was connected to one side of a differential pressure transducer (226A Baratron differential capacitance manometer, mKS Instruments, Andover, MA). The other side of the differential pressure transducer was connected to a ~1 L stainless steel cylinder to be used as a reference. The other end of the reference cylinder was connected to a solenoid (Skinner valve, model 71215SN2MN00N0, Parker, New Britain, CT) that was periodically opened and closed to refresh the pressure within the reference cylinder whenever the pressure transducer drifted out of range; the cylinder attached to the 50 cm inlet did not have a solenoid valve and instead was plugged. The transducers and reference volumes were placed in a control box that was buried ~0.5 m under the soil. A CR3000 datalogger (Campbell Scientific), located in a separate enclosure located on the soil surface, measured and recorded each differential pressure transducer at 1 Hz, and whenever the data for an inlet was out of range (> 500 Pa or < -500 Pa) the datalogger opened the corresponding solenoid for 2 seconds before closing it. The datalogger also recorded the temperature inside the buried control box with a thermistor (Temp 107 probe, Campbell Scientific) and the temperature within the 50 cm reference cylinder; instead of a solenoid on this cylinder there was a plug that encased and sealed a platinum resistance thermometer within it (Omega 100-ohm platinum-RTD, model RTD-810, with a Omega signal conditioning module, model OM5IP4-N100-C, Omega Engineering). This methodology provided differential pressure measurements between the soil pressure and a somewhat arbitrary reference pressure (i.e., the pressure captured within the reference cylinder at the time of the last opening/closing of the solenoid valve plus any temperature changes within he cylinder, as well as possible leaks and molecular exchange across the pressure sensor's diaphragm). A detailed description of the reconstruction of the absolute soil pressure is provided in the attribute accuracy report above.
Methodology_Citation:
Citation_Information:
Originator: Bristo, Keith L.
Publication_Date: 2002
Title:
Thermal conductivity
Geospatial_Data_Presentation_Form: book chapter
Other_Citation_Details:
pp 1209-1226
Larger_Work_Citation:
Citation_Information:
Originator: Dane, Jacob H. (Editor)
Originator: Topp, Clarke G. (Editor)
Publication_Date: 2002
Title:
Methods of soil analysis: Part 4. Physical methods
Geospatial_Data_Presentation_Form: book chapter
Publication_Information:
Publication_Place: Madison, WI
Publisher: Soil Science Socity of America, Inc.
Other_Citation_Details:
1744 pages
Methodology_Citation:
Citation_Information:
Originator: Topp, G.C.
Originator: Davis, J.L.
Originator: Annan, A.P.
Publication_Date: 1980
Title:
Electromagnetic determination of soil water content: Measurements in coaxial transmission lines
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Watershed Resources Research
Issue_Identification: 16(3): 574-582
Online_Linkage: https://doi.org/10.1029/wr016i003p00574
Source_Information:
Source_Citation:
Citation_Information:
Originator: University Corporation for Atmospheric Research / National Center for Atmospheric Research - Earth Observing Laboratory
Publication_Date: 2012
Title:
BEACHON 5 minute ISFS data, not tilt corrected
Edition: Version 1.0
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publisher: UCAR/NCAR - Earth Observing Laboratory
Other_Citation_Details:
Data provided by NCAR/EOL under the sponsorship of the National Science Foundation. https://data.eol.ucar.edu/
Online_Linkage: https://doi.org/10.5065/D6F769XG
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20090708
Ending_Date: 20120928
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
NCAR
Source_Contribution:
Ambient pressure at the NCAR Manitou Experimental Forest Observatory from 8 July 2009 until 28 September 2012 were obtained from: https://data.eol.ucar.edu/cgi-bin/codiac/fgr_form/id=496.003.
Process_Step:
Process_Description:
For soil temperature, 5-minute data were processed by removing outliers, corrected for panel voltage errors, filtered for noise, and resampled to 30-minutes. For soil thermal conductivity, the 1-Hz temperature and heating curves for each half-hour were fit to nonlinear heating/cooling equations, the resulting statistical fitting parameters were processed by removing outliers. For soil water content, the 5-minute data were processed by removing outliers, filtered for noise, and resampled to 30-minutes. For soil CO2, 30-minute data were processed by removing outliers and calibration corrected. For soil air pressure, 5-minute data were processed by removing outliers and used to estimate reference cell drifts; the 1-Hz data was subsequently corrected for reference cell drifts, and resampled to 5-minutes and 30-minutes. A more thorough description of each of these processing steps can be found in the attribute accuracy section above. Data referred to as “raw” are equivalent to the original measurement recorded by the data acquisition system while data referred to as “processed” have these steps applied.
Process_Date: 2020
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Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
Below you will find a list and description for the files available in this data publication.

DATA FILES

\Data\BEACHON_5min_Processed.csv: Comma-delimited ASCII text file containing continuous soil temperature and water measurements from the Manitou Experimental Forest, Colorado archived every 5-minutes. Measurements were taken from 2008 to 2014. The file contains 594,710 rows. Variables for this file are described in \Data\BEACHON_5min_Processed_Variables.csv.

\Data\BEACHON_5min_Raw.csv: Comma-delimited ASCII text file containing raw data archived for 5-minute soil temperature, water content, and pressure corrections plus 1-Hz temperature and heating curves used to calculate thermal conductivity. Measurements were taken from 2008 to 2014. The file contains 594,710 rows. Variables for this file are described in \Data\BEACHON_5min_Raw_Variables.csv.

\Data\BEACHON_30min_Processed.csv: Comma-delimited ASCII text file containing continuous soil temperature and water measurements from the Manitou Experimental Forest, Colorado summarized half-hourly. Measurements were taken from 2008 to 2014. The file contains 99,119 rows. Variables for this file are described in \Data\BEACHON_30min_Processed_Variables.csv.

\Data\SAP_1sec_Processed\BEACHON_p_yyyyddd.csv: Comma-delimited ASCII text files (1,122), containing processed 2011-2014 soil air pressure data. Filenames are based on the four digit year (yyyy) and the three digit Julian date (ddd = 1 to 365). Each file contains 84,600 rows of data corresponding to measurements recorded every 1 second over the duration of a day. All times are in Mountain Standard Time (MST). Variables for this file are described in \Data\BEACHON_p_yyyyddd_Variables.csv.

\Data\TC_1sec_RawBEACHON_TC_yyyyddd.csv: Comma-delimited ASCII text files (2,067), containing the raw 2008-2014 thermal conductivity (TC) data. Filenames are based on the four digit year (yyyy) and the three digit Julian date (ddd = 1 to 365). Each file contains 5,760 rows of data corresponding to measurements recorded every 1 second for the first 2 minutes of each half-hour throughout the day. All times are in MST. Variables for this file are described in \Data\BEACHON_TC_yyyyddd_Variables.csv.


DATA DESCRIPTION FILES

\Data\BEACHON_5min_Processed_Variables.csv: Comma-delimited ASCII text file containing a list and description of the variables in BEACHON_5min_Processed.csv.

\Data\BEACHON_5min_Raw_Variables.csv: Comma-delimited ASCII text file containing a list and description of the variables in BEACHON_5min_Raw.csv.

\Data\BEACHON_30in_Processed_Variables.csv: Comma-delimited ASCII text file containing a list and description of the variables in BEACHON_30min_Processed.csv.

\Data\SAP_1sec_Processed\_BEACHON_p_yyyyddd_Variables.csv: Comma-delimited ASCII text file containing a list and description of the variables in the BEACHON_p_yyyyddd.csv files.

\Data\TC_1sec_Raw\_BEACHON_TC_yyyyddd_Variables.csv: Comma-delimited ASCII text file containing a list and description of the variables in the BEACHON_TC_yyyyddd.csv files.


SUPPLEMENTAL FILES

\Supplements\2009-06-03-####JFrank-ManitouEF,CO-BEACHON-SoilPit*.jpg: JPEG image files (4) containing pictures of a soil pit from this study taken by John Frank on 06/03/2009. (#### represents picture number)

\Supplements\2009-07-08-####JFrank-ManitouEF,CO-BEACHON.jpg: JPEG image files (15) containing pictures of the collection equipment and site location taken by John Frank on 07/08/2009. (#### represents picture number)

\Supplements\StudyPlan_FWE-wjm-01-2008.pdf: Portable Document Format file containing the 2008 study plan for this project titled "Soil-Atmosphere Interactions: Soil heat flux and response of CO2 respiration fluxes to atmospheric forcing at Manitou Experimental Forest."
Entity_and_Attribute_Detail_Citation:
none provided
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Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Research and Development
Contact_Position: Research Data Archivist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect Road
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: see Contact Instructions
Contact Instructions: This contact information was current as of October 2020. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2020-0061
Distribution_Liability:
Metadata documents have been reviewed for accuracy and completeness. Unless otherwise stated, all data and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. However, neither the author, the Archive, nor any part of the federal government can assure the reliability or suitability of these data for a particular purpose. The act of distribution shall not constitute any such warranty, and no responsibility is assumed for a user's application of these data or related materials.

The metadata, data, or related materials may be updated without notification. If a user believes errors are present in the metadata, data or related materials, please use the information in (1) Identification Information: Point of Contact, (2) Metadata Reference: Metadata Contact, or (3) Distribution Information: Distributor to notify the author or the Archive of the issues.
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Digital_Transfer_Information:
Format_Name: ASCII
Format_Version_Number: see Format Specification
Format_Specification:
Comma-delimited ASCII text file (CSV)
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2020-0061
Digital_Form:
Digital_Transfer_Information:
Format_Name: JPG
Format_Version_Number: see Format Specification
Format_Specification:
Image file
File_Decompression_Technique: Files zipped with 7-Zip 19.0
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2020-0061
Digital_Form:
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Format_Name: PDF
Format_Version_Number: see Format Specification
Format_Specification:
Portable Document Format file
File_Decompression_Technique: Files zipped with 7-Zip 19.0
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Metadata_Reference_Information:
Metadata_Date: 20201013
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: John Frank
Contact_Organization: USDA Forest Service, Rocky Mountain Research Station
Contact_Position: Electronics Engineer
Contact_Address:
Address_Type: mailing and physical
Address: 240 W. Prospect Rd.
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: 970-498-1319
Contact_Electronic_Mail_Address: john.frank@usda.gov
Metadata_Standard_Name: FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001.1-1999
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