1. Data Set Overview 2. Investigator(s) 3. Theory of Measurements 4. Equipment 5. Site Description 6. Data Acquisition Methods 7. Observations 8. Data Description 9. Data Manipulations 10 Errors and Limitations 11. Software 12. References 13. Glossary of Terms and Acronyms 14. Document Information 1. Data Set Overview 1.1 Data Set Identification [This section is aimed toward the person searching for a data set. Descriptions should be succinct and clear, and acronyms should be spelled out.] Boreal Ecosystem Research and Monitoring Sites (BERMS) Tower Flux Meteorological Data From the Southern Study Area 2002 Harvested Jack Pine Site 1.2 Study Overview [A short text describing the study/experiment, and its objective] The BERMS (Boreal Ecosystem Research and Monitoring Sites) project was designed as a 5 year partial follow-up to the BOREAS (Boreal Ecosystem-Atmosphere Study) experiment. A need to study the effects of harvesting on the carbon, water and energy budgets in forested ecosystems resulted in the establishment of a new flux site near the Old Jack Pine site, which was harvested in 2000, and scarified in 2002. The data set documented here, includes the near-surface meteorological measurements at the 2002 Harvested Jack Pine site in support of carbon, water and energy flux measurements at this site. The climate monitoring program serves some of the following purposes: 1) to provide supporting measurements for flux monitoring, 2) to contribute to the development and validation of weather and climate models and 3) to provide information for interannual climate variability studies in the boreal forest. BERMS has been a participant in Fluxnet Canada since 2002. 1.3 Data Set Introduction [The nature of the data, including a summary of the key parameters/variables studied, and the primary instruments used. A full description will be given in section 7.] The main meteorological data set is in text format. Variables have been delimited by commas, to make it easy to import into most software programs. Files have been grouped by site, month and then by data type. For example, at 2002 Harvested Jack Pine in one month, there are three files: the first contains ANCILLARY data (extra data not normally required by users), the second contains the MAIN subset of measured variables and the third includes SUMMARIZED and gapfilled data. These files have two header lines, the first for variable names in APL (Adjective_Parameter_Location) format, and the second for units. Here is a summary of the measured parameters (most are measured at 30min intervals): -Air temperature: measured as deg C at various heights in relation to the structure of the forest canopy. -Humidity: measured as relative humidity at various heights in relation to the structure of the forest canopy. -Precipitation: snow depth, precipitation accumulation, rain events measured in mm. -Wind direction: measured in compass degrees above the forest canopy. -Wind speed: measured in meters per s above and within the forest canopy. -Atmospheric pressure: surface pressure measured in millibars (or Pascals). -Soil temperature: measured in deg C at 1 or more locations and at various depths in relation to ground level. -Radiation: measured in watts per m sq. Includes: net radiation, downwelling shortwave, upwelling shortwave, downwelling longwave, upwelling longwave, diffuse shortwave radiation, global solar radiation and photosynthetically active radiation. -Water table height: measured in mm (not installed yet, as of Mar/04). 1.4 Related Data Sets [Note any similar or related data collected by the investigator, other investigators, or other data centres. Something like five or six related data sets is a good number to provide.] 1) BERMS Old Jack Pine, 1994 Harvested Jack Pine, and 1975 Harvested Jack Pine, Fluxtower measurements. *** More to be added later *** 2. Investigator(s) 2.1 Principal Investigator(s) Name and Title [Identify the Principal Investigator(s) for this data set, including general affiliation if applicable] Alan Barr (PI) Climate Resarch Branch Environment Canada National Hydrology Research Centre 11 Innovation Boulevard Saskatoon, SK S7N 3H5 Canada Alan.Barr@ec.gc.ca (306)975-4324 2.2 Title of Investigation [Official name of group taken from the Fluxnet-Canada Experiment Plan.] BERMS HJP 2002 Meteorological data. 2.3 Contact Information [Identify and give full coordinates of the person(s) most knowledgeable about the actual collection and processing of the data sets. In many cases this will be a person (or persons), other than the Principal Investigator.] Erin Thompson BERMS Secretariat Climate Resarch Branch Environment Canada National Hydrology Research Centre 11 Innovation Boulevard Saskatoon, SK S7N 3H5 Canada Erin.Thompson@ec.gc.ca (306)975-4215 Charmaine Hrynkiw Climate Resarch Branch Environment Canada National Hydrology Research Centre 11 Innovation Boulevard Saskatoon, SK S7N 3H5 Canada Charmaine.Hrynkiw@ec.gc.ca (306)975-5627 2.4 Field and/or laboratory staff: Saskatoon: Dell Bayne, Bruce Cole, Joe Eley, Natasha Neumann, Craig Smith, Erin Thompson, Steve Enns. 2.5 Acknowledgements : Students: Jodi Axelson, Andrea Eccleston, Matt Regier, Jenny Hill, Courtney Campbell, Lisa Christmas, Kim Kovacs, Justin Beckers, Brett Reynolds. --------------------------------------------------------------------------- 3. Theory of Measurements [Theoretical basis for the way in which the measurements were made (e.g. special procedures, characteristics of the instrument, etc.).] Meteorological measurements were taken in order to understand the general climate of the Canadian boreal region and provide supporting measurements to compute carbon, water and energy fluxes. Since many different instruments were used to measure meteorological data, please refer to the user manuals referenced in the reference section for details on operation. See section on Equipment below for summarized information. --------------------------------------------------------------------------- 4. Equipment 4.1.1 Sensor/Instrument Description, Manufacturer, Calibration, Specs [This section provides a listing of the instrumentation and the characteristics of the instrumentation.] Automated stations were set up to log data from meteorological sensors. These data was either downloaded remotely via modem or stored on modules until they could be downloaded to a computer. Various types of instruments were used to measure the following variables A) temperature and humidity, B) precipitation, C) radiation, D) soil heat flux, E) wind speed and direction F) Campbell Scientific data loggers. (description, manufacturer, calibration, specs, frequency of calibration, other calibration information) A)TEMPERATURE and HUMIDITY: i)HMP35CF Temp/Humidity Probe, ii) Copper-Constantan Thermocouples, iii)237/237F Wetness Sensing Grid i) HMP45C Temperature/Humidity Probe -Description: This probe contains a Platinum Resistance Temperature detector (PRT) and a Vaisala HUMICAP 180 capacitive relative humidity sensor. -Manufacturer: Campbell Scientific -Calibration: Factory calibrated. Tested by MSC Saskatoon prior to deployment in the field. -Specs (PRT): 1000 Ohms PRT, IEC 751 1/3 Class B; Temp Measurement Range: -40 to +50 deg C; Temp Output signal Range: 0.008 to 1V; Temp Accuracy: +/- 0.2 to 0.5 deg C -Specs (Humicap): RH Measurement Range: 0 to 100% non-condensing; RH Output Signal Range: 0.008 to 1 VDC; Accuracy at 20 deg C: +/-2% RH (0 to 90% RH) and +/-3% RH (90 to 100% RH); Temperature Dependence of Relative Humidity Measurement: +/-0.05% RH/degC; Typical Long Term Stability: Better than 1% RH per year; Response Time (at 20 deg C, 90% response): 15 seconds with membrance filter -Frequency of Calibration: Factory calibrated prior to purchase only. ii) Copper-Constantan Thermocouples: - Description: Copper-Constantan thermocouples were used for measuring soil temperature and air temperature. The soil thermocouples were 105T welded junction thermocouple probes. The air thermocouples were constructed by soldering Copper-Constantan thermocouple wire junctions, and insulating the junction with silicone. - Manufacturer (Soil thermocouples): Campbell Scientific. - Manufacturer (Air thermocouples): Campbell Scientific?, 30 AWG wire. - Manufacturer (Snow Temp profile thermocouples): Thermocouple junction constructed at Queen's University, Kingston, Ontario? - Calibration: n/a. - Specs: Campbell Scientific 105T welded junction thermocouple probe. Range: -78 deg C to 100 deg C. Accuracy 0.13 deg F. - Frequency of Calibration: n/a. - Other Calibration information: n/a. iii) 237/237F Wetness Sensing Grid -Description: The wetness sensor was used to determine the amount of moisture at the ground surface. It was intended to give information which would supplement the measurments taken by the radiation sensors becasue moisture affects the longwave radiation measurments. -Manufacturer: Campbell Scientific. -Calibration: Not Calibtrated -Specs: consists of a rigid epoxy circuit board with interlacing gold-plated copper fingers. This model is an artificial leaf type suitable for use with CR7, CR10,and 21X dataloggers. Range: two sclaes have been used to obtain readings; 0-5 mV, the sensor will read ~2.5mV when measurably damp and ~4.95mV when very damp. 0-100 Kohms, 100 being measurably damp and 1 being high moisture. -Frequency of Calibration: n/a -Other Calibration Information: The data is quantitatively defined iv) 107 Temperature Probe - Description: 107 Temperature probe contains a Fenwal Electonics UUT51J1 thermistor (Campbell Scientific, 1983). - Manufacturer: Campbell Scientific - Calibration: factory calibration prior to purchase? - Specs: 107 Temperature probe resolution: 0.001 deg C. Accuracy: +/-0.4 deg C over the range of ?33 to 48 deg C (overall accuracy is better than +/-0.2 deg C. The bridge resistors are 0.1% tolerance with a 10ppm temperature coefficient. (Campbell Scientific, 1983) B)PRECIPITATION - i) Tipping Bucket Rain Gauge, ii) SR50 Snow Depth Sensor, iii) Geonor T-200 i) Tipping Bucket Rain Gauge Model 525M - Description: Is a smaller adaptation of the standard Weather Bureau Tipping Bucket Rain Gauge. It measures rainfall at rates up to 2" per hour with an accuracy of +/- 1%. Output is a switch closure for each bucket tip. A tip occurs with each .1mm of rain (Campbell Scientific, 1996). - Manufacturer: Texas Electronics Inc. - Calibration: Factory Calibrated. - Specs: Range: infinite increments of .1mm; Accuracy: 1% at 2" per hour or less; Signal output: momentary switch closure activated by the tipping bucket mechanism. Switch closure is approximately 135ms. - Frequency of Calibration: Tested in controlled lab conditions prior to deployment in field or if measurements were suspect. Necessary adjustments applied to increase or decrease the amount of tips. Not officially re-calibrated. ii) SR50 Snow Depth Sensor -This sensor measures the distance from the sensor to a target. The SR50 determines the distance to a target by sending out ultrasonic pulses and listening for the returning echoes that are reflected from the target. The time from transmissions to return of an echo is the basis for obtaining the distance measurement. Since the speed of sound in air varies with temperature, an independent temperature measurement is required to compensate the distance reading. A simple calculation is applied to initial reading simple calculation is applied to initial readings for this purpose. -Manufacturer: Campbell Scientific -Calibration: Factory calibrated. -Specs: Range: 0.5 to 10m; Accuracy: +/- 1cm or 0.4% of distance to target (whichever is greatest) requires external temperature compensation; Resolution: 0.1mm; Beam Acceptance Angle: Approx 22 deg; Operating Temperature: -30 to +50 deg C Standard; Dimensions: Length 31cm Diameter 7.5cm; Weight: 1.3kg. -Frequency of Calibration: Factory calibrated once and tested at MSC Saskatoon prior to deployment in the field. Distances from sensor to target occasionally checked in the field. iii) Geonor T-200 -Description: Is an automatically recording all weather precipitation gauge. The Geonor T-2000 uses vibrating wire sensors to detect changes bucket weight indicating a precipitation event. The precipitation is melted in the container partly filled with antifreeze and topped with a low viscosity oil to impede evaporation. Precipitation can be measured at any interval, allowing for accurate measurments of precip intensity. (Geonor, 1995) -Manufacturer: Geonor -Calibration: Factory calibrated prior to deployment. Geonor also supplies calibration equations which are inputted in field to convert frequency values to precipitation result. -Specs: Capacity: 0-600mm (including antifreeze liquid). Collecting area: 200cm2. Sensitivity: 0.1mm. Accuracy: 0.1%FS. Repeatability: 0.1mm. Temp Range: Sensor -25 deg C to 60 deg C. Temp drift: 0.001%FS/deg C. Materials: Aluminum alloy. Mounting: Universal 3-point with leveling system incorporated in base. -Frequency of calibration: Factory calibrated and then calibration calculations inputted into data logger in field. C)RADIATION- i)Middleton CNR-1 Net Radiometer i) Middleton CNR-1 Net Radiometer - Description: The Middleton CNR-1 is a pyrradiometer for the measurement of net total radiation flux (solar, terrestrial, and atmospheric). It can be used for portable or stationary applications (Carter-Scott Design, 1995) - Manufacturer: Carter-Scott Design - Calibration: Factory Calibrated. - Specs: Sensitivity: 35 to 45 microvolts/Watts per m sq; Impedance: 70-80 Ohms; Response Time: 45s @ 95%; Non-linearity: <+/-1% at 500 W per m sq; Operating Temperature: -40 to +60 deg C; Cosine Response: 4% of ideal; Spectral Range: 0.3 to 60 micro m. - Frequency of Calibration: Factory calibrated once prior to deployment in field and then calibrated at NARC in 1996?. D)SOIL HEAT FLUX- i) Middleton CN3 Heat Flux Plate ii) Hukseflux Thermal Sensor i) Middleton CN3 Heat Flux Plate - Description: Heat transfer occurs by conduction, convection, or radiation. The CN3 Heat Flux Plate is designed to directly measure the conductive heat transmission in the medium in which the sensor is embedded. It is small and thin to offer minimal disturbance to the heat flow pattern. A temperature difference between the top and bottom faces of the CN3 generates a DC voltage from the sensor thermopile. The temperature difference is proportional to the heat flow in the medium, and the polarity of the output voltage changes in accordance with the direction of the heat flow (Carter-Scott Design). - Manufacturer: Carter-Scott Design - Calibration: Factory calibrated. - Specs: Sensitivity: 21 microV/W.m2 (typical) in fine dry sand; Impedance: 23 Ohms (typical); Temperature Range: -20 to +70 deg C; Thermal Conductivity: .4W/m.deg C; Temperature Error: .2%/deg C; Response Time: 30sec. To 95% (in air); Sensor Thermopile: copper-constantan (250 junctions). - Frequency of Calibration: Factory calibrated once prior to installation ii) Hukseflux Thermal Sensor -Description: The HFPO1 heat flux plate serves to measure the heat flux that flows throught the object in which it is incorporated or on which it is mounted. The flux is expressed in Wattes per sqaure meter. HFPO1 is especially designed for use inside walls and inside the soil. (Hukseflux Thermal Sensors, 2000) -Manufacturer: Hukseflux Thermal Sensors -Calibration:Factory calibration -Specs: Range: +2000 to - 2000 w/m2. Accuracy: Meteorological: +/- 20% for daily totals over a thermal conductivity range of the medium from 0.1 to 1.7 W/mK and the full temperature range. Building Physics: Better than +/- 20%, when correcting for the resistance error. Specified measurments: Heat Flux in Watts per meter squared, perpendicular to the sensor surface. Temperature dependence: < 0.1 %/deg C -Frequency of calibration: Recomended recalibration every two years. E)WIND SPEED AND DIRECTION i) RMY Propeller Anemometer Model 05103 (Speed and Dir) - Description: Is a 4-blade helicoid propeller. Propeller rotation produces an AC sine wave voltage signal with frequency directly proportional to wind speed. The wind direction sensor is a lightweight vane with a sufficiently low aspect ratio. - Manufacturer: R.M. Young - Calibration: Factory Calibrated - Specs: Range: 0-60 m/s and 360 deg, Accuracy: +/-0.3m/s and +/-3deg - Frequency of Calibration: once prior to deployment. F) CAMPBELL SCIENTIFIC DATA LOGGERS - Description: provides the means to log information from sensors whose leads are connected to I/O cards. Control module functions include real-time task initiation, measurement processing, data storage, telecommunications and keyboard/display interaction. - Manufacturer: Campbell Scientific - Calibration: n/a - Specs: n/a - Frequency of Calibration: 4.1.2 Manufacturer of Sensor/Instrument [Name, address, and telephone number of the company that produced the instrument. If the measuring device was built by the investigator, or specially customized, please specify.] See section above. 4.1.3 Principles of Operation [Fundamental scientific basis for the way the instrument operates. This is a summary; where a full development is required, it should be placed in section 3.] See section above. 4.1.4 Source/Platform [What the instrument(s) is(are) mounted on, e.g. tower, hand held, aircraft.] - Most of the meteorological instruments were installed on a 3.2m single scaffold tower with a ladder on the outside. This tower was equipped with AC power and had a heated hut nearby, also with AC power. Parameters measured on this tower included: air temperature, humidity, radiation, wetness and wind. - Precipitation gauges: SR50 Snow Depth Sensor was installed on a 2 m high pole (pole installed in the ground) on the South side of the communications tower (a traingular radio tower), with a CNR1 net radiometer mounted on it at 6m.The TBRG gauge was placed on the ground just slightly South East of the SR50. - Soil temperature, Soil moisture and soil heat flux, were measured below ground level, near the tower. - Dataloggers were housed in the above mentioned heated hut For more details see section on Data Description 4.1.5 Sensor/Instrument Measurement Geometry [Describe the sensor location(s), orientation, and any other parameters that affect the collection or analysis of data, e.g. field of view, optical characteristics, height, etc.] - Most above ground instruments, such as air temperature, wind and radiation sensors were installed on a 3.2 m tall single scaffold tower.The exceptions were near ground measurements, below 2m. These sensors were installed near the tower, on their own platforms. All sensors were installed to optimize measurement requirements. -Soil moisture, ground heat flux and soil temperature sensors were installed below the ground, beneath organic layers of leaf litter. See the section on Data Description for more information. 4.1.6 Collection Environment [Under what environmental conditions were the data collected and the instrumentation operated. This includes descriptions of the types of sites visited and factors that may effect the measurements such as temperature range experienced during data collection.] Temperatures ranged from a maximum of 35 deg C in the summer to a minimum of -45 deg C in the winter. On average, the region has a frost-free season of between 80 to 100 days (Phillips, 1990). Precipitation events in the summer ranged from trace amounts to approximately 35mm. Summer storms consisted of wind gusts up to 15 m per s, with rain, lightning and/or hail. In the winter it was common to have periods of snow, ice and frost. The average maximum snow depth for the region is between 50 and 70cm (Gray, 1981). Most of the instrumentation was exposed to these elements, with the exception of dataloggers and the instrumentation installed below the ground. 4.2 Calibration [Describe how the measurements made by the device(s) are calibrated with known standards. Specific details should be given in the subsections below.] See section on Equipment above. 4.2.1 Specifications [Record any specifications that affect the calibration of the device, its operations, or the analysis of the data collected with it.] See section on Sensor/Instrument Description above. 4.2.1.1 Tolerance [Describe the acceptable range of inputs and the precision of the output values.] See section on Sensor/Instrument Description above. 4.2.2 Frequency of Calibration [Indicate how often the instrument is measured against a standard. Also indicate any other routine procedures required to maintain calibration or detect miscalibrations. Describe also the actual practice with this device.] See section on Sensor/Instrument Description above. 4.2.3 Other Calibration Information [Give factory calibration coefficients, information about independent calibrations, history of modifications, etc.] See section on Sensor/Instrument Description above. --------------------------------------------------------------------------- 5 Site description [Standard site description, should include site location in a well referenced coordinate system, site elevation, vegetation type, etc...] - Location 55km N of Smeaton. Lat: 53.944737 N, Long: -104.649340 W (Laura Chasmer - survey grade GPS), elev: 579.27m. - Topography: undulating - Predominant vegetation: Herbaceous colonizers and bare soil (severely disturbed due to scarification. - Soil properties: Sandy soil with very good drainage. The organic layer is mostly absent or turned under as a result of scarification. ------------------------------------------------------------------------------ 6. Data Acquisition Methods [Describe the procedures for acquiring this data in sufficient detail so that someone else with similar equipment could duplicate your measurements. Should be sufficient to include in the Methods section of a paper] 6.1 Methods of data acquisition [Describe the procedures for acquiring this data in sufficient detail so that someone else with similar equipment could duplicate your measurements. Should be sufficient to include in the Methods section of a paper] Instrumentation connected to Campbell Scientific data loggers were sampled and stored on the loggers. Data were either downloaded daily from dataloggers through dial-up modems using Campbell Scientific software (OA, OBS, OJP, HJP94) or via satellite internet connections using customized scheduled ftp transfers (FEN, HJP75, HJP02). In cases where a datalogger was not connected to a phone line or internet connection, data were downloaded either by a lap-top computer or storage module. 6.2 Sampling 6.2.1 Spatial Coverage/Geographic Location [Give enough information to locate the measurement site with suitable precision. This may be a list of sites visited, or a geographic range in the case of aircraft measurements or satellite imagery, or plot coordinates in UTM, including a clear reference to the coordinate system.] Instrumentation was installed within 50m of the main tower location. - Location: 55km N of Smeaton (Lat: 53.908 deg N, Long: 104.656 deg W, elev: 579.27m) For more details on exact location of instruments, see section on Data Description. 6.2.2 Spatial sampling [Includes a description of spatial sampling: how many sites/samples; how were they selected, the coordinates (e.g. UTM) of the plots, how many replicates over space, etc...] See section on Data Description for more information. 6.2.3 Temporal coverage [The period(s) of time during which data was collected more or less continuously.] Data was continuously collected all year round. 6.2.4 Temporal sampling [Includes a description of the temporal sampling scheme: when was the sampling carried out (time of day), at what frequency were the measurements taken, how long did the measurements take, etc...] Most meteorological variables were sampled every 5seconds and averaged over 30min intervals. The exception to this would be snow depth and cumulative precipitation. --------------------------------------------------------------------------- 7 . Observations 7.1 Procedural Notes [Use this section to record observations made during actual data collection, which could bear on the analysis of the data, e.g. condition of site, peculiar procedures or operations, the presence of U.F.O.'s or bears, oddities in equipment function, etc.] n/a 7.2 Field Notes [If a large amount field notes exist, a reference to a separate file will be adequate.] See FieldNotes.txt --------------------------------------------------------------------------- 8 . Data Description [This section describes the data in the data set: what the data are, units, format, data characteristics.] 8.1 Data Organization [Describe how your data is organized, e.g.: by site and/or month.] Data are organized by site and month. Three types of files are available: i)Ancillary: a subset of extra Meteorological variables that were used to derive and quality assure some variables in the Main directory. These variables would not normally be used by most people, but are valuable enough to keep in the archive. ii)Main: contains the most complete sub set of meteorological variables where most have been corrected and some have been derived, but none have been gap-filled. iii)Summarized: contains data that have been summarized from the Main subset. Variables have been aggregated (eg. 4 tower top temperature measurements have become one) and gaps have been filled. Most variables are not available yet (as of Mar/04). 8.2 Image and Data Format [Specify the format that the image or the data is (are) provided in.] Data are comma delimited ASCII format. 8.3 Numerical Data Characteristics [Describe the types of data submitted. On separate lines, indicate each column number followed by its header, the variable description, the unit of measurement or format of presentation, the data source or sensor, and the variable range.] Note that there are three types of Meteorology files available: 1) Ancillary 2) Main and 3) Summarized (see Data Organization section above). All three are included below. This information may also be found in the "readme.txt" files found under each file type's directory. 1) Ancillary Variable List: 1 DataType="Met1" (n/a) Includes "raw" variables used to compute some other variables (corrections applied but gaps not filled.) 2 Site="SK-HJP02" (n/a) Saskatchewan Harvested Jack Pine Site 2002. 3 SubSite="FlxTwr" (n/a) Flux Tower sub-site. 4 Year (UTC) 4 digit year. 5 Day (UTC) Day of Year. 6 End_Time (UTC) End of 30min time period, in hours and minutes UTC. 7 CNR1_DownLong (W/m2) Downwelling Longwave Radiation; 6m above ground on a boom extending wave_Thermopile from the telephone tower. 8 CNR1_BodyPRT (degC) CNR-1 Instrument Body Temp; 6m above ground on a boom extending Temp from the telephone tower. 9 CNR1_UpLong (degC) Upwelling Longwave Radiation; 6m above ground on a boom extending wave_Thermopile from the telephone tower. 10 BoomPitch_6m (mV) Pitch of radiation sensor, a measure of levelness. 11 BoomRoll_6m (mV) Roll of radiation sensor, a measure of levelness. 12 MetLoggerTemp (degC) Internal Meteorological Datalogger Temperature. 13 Soil_RefTemp_ (degC) AM25T Multiplexer temperature, used as a reference temperature Mplexer for soil thermocouples. 14 Misc_RefTemp_ (degC) AM25T Multiplexer temperature, used as a reference temperature Mplexer for snow thermocouples, tower thermocouples and soil heat flux. 15 MetLogger (Volts) Meteorological Datalogger Battery Voltage - not recorded. Battery 16 SoilLogger (Volts) Soil Datalogger Battery Voltage. Battery 17 Certification (n/a) CPI: checked by PI; PRE: preliminary. Code 18 RevisionDate (dymo Date data last revised by PI. year) 2) Main 1 DataType="Met2" (n/a) Second subset of meteorological data corrections applied but gaps not filled. 2 Site="SK-H02" (n/a) Saskatchewan Harvested Jack Pine Site 2002. 3 SubSite="FlxTwr" (n/a) Flux Tower sub-site. 4 Year (UTC) 4 digit year UTC. 5 Day (UTC) Day of Year UTC. 6 End_Time (UTC) End of 30min time period, in hours and minutes UTC. 7 FourWay_Net (W/m2) Derived by: (downwelling shortwave Rad_AbvCnpy - upwelling shortwave)+(downwelling longwave - upwelling longwave). 8 GlobalShort (W/m2) Global Shortwave Radiation; waveRad_Abv 6m above ground on a boom extending Cnpy_6m from the telephone tower. 9 UpShortwave (W/m2) Upwelling Shortwave Radiation; Rad_AbvCnpy 6m above ground on a boom extending _6m from the telephone tower. 10 DownLongwave (W/m2) Downwelling Longwave Radiation; 6m Rad_AbvCnpy above ground on a boom extending _6m from the telephone tower. 11 UpLongwaveRad (W/m2) Upwellinh Longwave Radiation; 6m _AbvCnpy_6m above ground on a aboom extending from the telephone tower. 12 Wetness_ (n/a) AVg Wetness; a yes or no measure of frost, AbvCnpy_6m dew, etc telling us if the radiation dome is obscured. 13 Tc_AirTemp_ (degC) Air Temperature; on walk-up tower, 4m AbvCnpy_4m above ground. 30 gauge Cu-Co wire thermocouple in gill aspirated radiation shield. 14 Tc_AirTemp_ (degC) Air Temperature; on walk-up tower, 1m AbvCnpy_1m above ground. 30 gauge Cu-Co wire thermocouple in gill aspirated radiation shield. 15 HMP_AirTemp_ (degC) Air Teperature; top of walk up tower, on railing AbvCnpy_4m 4m above ground. Vaisala HMP in a gill radiation shiled. 16 HMP_AirTemp_ (degC) Air Temperature; on walk up tower, on railing AbvCnpt_1m 1m above ground. Vaisala HMP in a gill radiation shield. 17 RelHum_Abv (%) Relative Humidity; top of walk-up tower Cnpy_4m on railing at 4m above ground. Vaisala HMP in a gill radiation shield. 18 RelHum_Abv (%) Relative Humidity; on walk-up tower, on railing Cnpy_1m 1m above ground. Vaisala HMP in a gill rad- iation shield. 19 WindSpd_Abv (m/s) Wind Speed Tower Top; mounted on a pipe extend- Cnpy_6m ing above the top platform of the walk up tower, at 6m above ground. RM Young pro- peller anemometer. 20 WindDir_Abv (deg) Wind Direction Tower Top; same as Wind Speed Tower Cnpy_6m Top.RM Young Propeller Anemometer 21 StdDev_Wind (deg) Standard Deviation of Wind Direction at Tower Top; Dir_AbvCnpy same as Wind Speed Tower Top. RM Young Propeller Anemometer. _6m 22 TBRG_Rain (mm) Tipping Bucket Rainfall over the 30min period; on a metal pipe 40ft NE of the communication tower at a 1m agl. Tipping Bucket Rain Gauge TBRG 525M, changed to CSI CS700-L Rain Gauge on Sept4, 2002. 23 GEONOR_Precip (mm) All Precipitation over 30min period; on a stand approx 25m from NE corner of hut. 24 SnowDepth (mm) Snow Depth; on a boom extending E from the communications tower, 205cm agl. 25 SoilTemp (degC) Soil Temperature; 2cm below ground _SWrod_2cm surface in a pit SW of tower. Queen’s Univ-made thermocouple mounted on a rod. 26 SoilTemp (degC) Soil Temperature; 5cm below ground _SWrod_5cm surface in a pit SW of tower. Queen’s Univ-made thermocouple mounted on a rod. 27 SoilTemp (degC) Soil Temperature; 10cm below ground _SWrod_10cm surface in a pit SW of tower. Queen’s Univ-made thermocouple mounted on a rod. 28 SoilTemp (degC) Soil Temperature; 20cm below ground _SWrod_20cm surface in a pit SW of tower. Queen’s Univ-made thermocouple mounted on a rod. 29 SoilTemp (degC) Soil Temperature; 50cm below ground _SWrod_50cm surface in a pit SW of tower. Queen’s Univ-made thermocouple mounted on a rod. 30 SoilTemp (degC) Soil Temperature; 100cm below ground _SWrod_100cm surface in a pit SW of tower. Queen’s Univ-made thermocouple mounted on a rod. 31 SoilTemp (degC) Soil Temperature; 2cm below ground _SErod_2cm surface in a pit SE of tower. Queen’s Univ-made thermocouple mounted on a rod. 32 SoilTemp (degC) Soil Temperature; 5cm below ground _SErod_5cm surface in a pit SE of tower. Queen’s Univ-made thermocouple mounted on a rod. 33 SoilTemp_ (degC) Soil Temperature; 10cm below ground _SErod_10cm surface in a pit SE of tower. Queen’s Univ-made thermocouple mounted on a rod. 34 SoilTemp (degC) Soil Temperature; 20cm below ground _SErod_20cm surface in a pit SE of tower. Queen’s Univ-made thermocouple mounted on a rod. 35 SoilTemp (degC) Soil Temperature; 50cm below ground _SErod_50cm surface in a pit SE of tower. Queen’s Univ-made thermocouple mounted on a rod. 36 SoilTemp (degC) Soil Temperature; 100cm below ground _SErod_100cm surface in a pit SE of tower. Queen’s Univ-made thermocouple mounted on a rod. 37 SoilTemp (degC) Soil Temperature; 2cm below the ground _S_2cm surface in a pit S of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 38 SoilTemp (degC) Soil Temperature; 5cm below ground _S_5cm surface in a pit S of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 39 SoilTemp (degC) Soil Temperature; 10cm below ground _S_10cm surface in a pit S of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 40 SoilTemp (degC) Soil Temperature; 2cm below ground _E_2cm surface in a pit E of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 41 SoilTemp (degC) Soil Temperature; 5cm below ground _E_5cm surface in a pit E of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 42 SoilTemp (degC) Soil Temperature; 10cm below ground _E_10cm surface in a pit E of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 43 SoilTemp (degC) Soil Temperature; 2cm below ground _SW_2cm surface in a pit SW of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 44 SoilTemp_ (degC) Soil Temperature; 5cm below ground _SW_5cm surface in a pit SW of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 45 SoilTemp (degC) Soil Temperature; 10cm below ground _SW_10cm surface in a pit SW of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 46 SoilTemp (degC) Soil Temperature; 2cm below ground _SE_2cm surface in a pit SE of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 47 SoilTemp (degC) Soil Temperature; 5cm below ground _SE_5cm surface in a pit SE of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 48 SoilTemp (degC) Soil Temperature; 10cm below ground _SE_10cm surface in a pit SE of tower (measured in conjunction with soil heat flux). Queen’s Univ-made thermocouple. 49 SnowTemp (degC) Snow Temp; 1cm above ground on rod _SW_1cm installed SW of Tower. Cu-Co thermo- couple. 50 SnowTemp (degC) Snow Temp; 2cm above ground on rod _SW_2cm installed SW of Tower. Cu-Co thermo- couple. 51 SnowTemp (degC) Snow Temp; 5cm above ground on rod _SW_5cm installed SW of Tower. Cu-Co thermo- couple. 52 SnowTemp (degC) Snow Temp; 10cm above ground on rod _SW_10cm installed SW of Tower. Cu-Co thermo- couple. 53 SnowTemp (degC) Snow Temp; 20cm above ground on rod _SW_20cm installed SW of Tower. Cu-Co thermo- couple. 54 SnowTemp (degC) Snow Temp; 30cm above ground on rod _SW_30cm installed SW of Tower. Cu-Co thermo- couple. 55 SnowTemp (degC) Snow Temp; 30cm above ground on rod _SW_30cm installed SW of Tower. Cu-Co thermo- couple. 56 SnowTemp (degC) Snow Temp; 50cm above ground on rod _SW_50cm installed SW of Tower. Cu-Co thermo- couple. 57 SnowTemp (degC) Snow Temp; 1cm above ground on rod _SE_1cm installed SE of Tower. Cu-Co thermo- couple. 58 SnowTemp (degC) Snow Temp; 2cm above ground on rod _SE_2cm installed SE of Tower. Cu-Co thermo- couple. 59 SnowTemp (degC) Snow Temp; 5cm above ground on rod _SE_5cm installed SE of Tower. Cu-Co thermo- couple. 60 SnowTemp (degC) Snow Temp; 10cm above ground on rod _SE_10cm installed SE of Tower. Cu-Co thermo- couple. 61 SnowTemp (degC) Snow Temp; 20cm above ground on rod _SE_20cm installed SE of Tower. Cu-Co thermo- couple. 62 SnowTemp (degC) Snow Temp; 30cm above ground on rod _SE_30cm installed SE of Tower. Cu-Co thermo- couple. 63 SnowTemp (degC) Snow Temp; 40cm above ground on rod _SE_40cm installed SE of Tower. Cu-Co thermo- couple. 64 SnowTemp (degC) Snow Temp; 50cm above ground on rod _SE_50cm installed SE of Tower. Cu-Co thermo- couple. 65 RevisionDate (dymo Date data last revised by PI. year) 3) Summarized 1 DataType (n/a) 2 Site (n/a) 3 SubSite (n/a) 4 Year (UTC) 5 Day (UTC) 6 End_Time (UTC) 7 FourWay_NetRad_AbvCnpy (W/m2) 8 CNR1_GlobalShortwaveRad_AbvCnpy_2m (W/m2) 9 LI_DownPAR_AbvCnpy_3m (umol/m2/s) 10 AirTemp_AbvCnpy_2m (degC) 11 RelHum_AbvCnpy_2m (%) 12 SpecificHum_AbvCnpy (g/kg) 13 WindSpd_AbvCnpy_5m (m/s) 14 SoilTemp_2cm (degC) 15 SoilTemp_5cm (degC) 16 SoilTemp_10cm (degC) 17 SoilTemp_20cm (degC) 18 SoilTemp_50cm (degC) 19 SoilTemp_100cm (degC) 20 Geonor_CumPrec (mm) 21 EventPrec (mm) 22 CertificationCode (n/a) 23 RevisionDate (dymoyear) 4) Gap Filled Meteorology 1 DataType (n/a) 2 Site (n/a) 3 SubSite (n/a) 4 Year (UTC) 5 Day (UTC) 6 End_Time (UTC) 7 GapfilledPIPref_FourWay_NetRad_AbvCnpy_2m (W/m2) 8 GapfilledPIPref_GlobalShortwaveRad_AbvCnpy_2m (W/m2) 9 GapfilledPIPref_UpShortwaveRad_AbvCnpy_2m (W/m2) 10 GapfilledPIPref_DownLongwaveRad_AbvCnpy_2m (W/m2) 11 GapfilledPIPref_UpLongwaveRad_AbvCnpy_2m (W/m2) 12 GapfilledPIPref_LI_DownPAR_AbvCnpy_3m (umol/m2/s) 13 GapfilledPIPref_LI_UpPAR_AbvCnpy_2m (umol/m2/s) 14 GapfilledPIPref_Tc_AirTemp_AbvGnd_2m (degC) 15 GapfilledPIPref_HMP_AirTemp_AbvCnpy_2m (degC) 16 GapfilledPIPref_HMP_AirTemp_AbvGnd_1m (degC) 17 GapfilledPIPref_RelHum_AbvCnpy_2m (%) 18 GapfilledPIPref_RelHum_AbvGnd_1m (%) 19 GapfilledPIPref_WindSpd_AtPrecip (m/s) 20 GapfilledPIPref_WindSpd_AbvCnpy_5m (m/s) 21 GapfilledPIPref_WindDir_AbvCnpy_5m (deg) 22 GapfilledPIPref_SurfPress (kPa) 23 GapfilledPIPref_QCdGeonor_CumPrec (mm) 24 GapfilledPIPref_SnowDepth (mm) 25 GapfilledPIPref_SoilTemp_S_2cm (degC) 26 GapfilledPIPref_SoilTemp_S_5cm (degC) 27 GapfilledPIPref_SoilTemp_S_10cm (degC) 28 GapfilledPIPref_SoilTemp_S_20cm (degC) 29 GapfilledPIPref_SoilTemp_S_50cm (degC) 30 GapfilledPIPref_SoilTemp_S_100cm (degC) 31 GapfilledPIPref_SoilTemp_W_1cm (degC) 32 GapfilledPIPref_SoilTemp_W_3cm (degC) 33 GapfilledPIPref_SoilTemp_W_5cm (degC) 34 GapfilledPIPref_SoilTemp_NE_2cm (degC) 35 GapfilledPIPref_SoilTemp_NE_5cm (degC) 36 GapfilledPIPref_SoilTemp_NE_10cm (degC) 37 GapfilledPIPref_SoilTemp_NE_20cm (degC) 38 GapfilledPIPref_SoilTemp_NE_50cm (degC) 39 GapfilledPIPref_SoilTemp_NE_100cm (degC) 40 GapfilledPIPref_SoilTemp_N_2cm (degC) 41 GapfilledPIPref_SoilTemp_N_5cm (degC) 42 GapfilledPIPref_SoilTemp_N_10cm (degC) 43 GapfilledPIPref_SoilTemp_E#1_2cm (degC) 44 GapfilledPIPref_SoilTemp_E#1_5cm (degC) 45 GapfilledPIPref_SoilTemp_E#1_10cm (degC) 46 GapfilledPIPref_SoilTemp_E#2_1cm (degC) 47 GapfilledPIPref_SoilTemp_E#2_3cm (degC) 48 GapfilledPIPref_SoilTemp_E#2_5cm (degC) 49 CertificationCode (n/a) 50 RevisionDate (dymoyear) 8.3.1.6 Sample Data Record DataType,Site,SubSite,Year,Day,End_Time,FourWay_NetRad_AbvCnpy,CNR1_GlobalShortwaveRad_AbvCnpy_6m,CNR1_UpShortwaveRad_AbvCnpy_6m,CNR1_DownLongwaveRad_AbvCnpy_6m,CNR1_UpLongwaveRad_AbvCnpy_6m,Wetness_AbvCnpy_6m,Tc_AirTemp_AbvCnpy_4m,HMP_AirTemp_AbvCnpy_4m,Tc_AirTemp_AbvGnd_1m,HMP_AirTemp_AbvGnd_1m,RelHum_AbvCnpy_4m,RelHum_AbvGnd_1m,WindSpd_AbvCnpy_6m,WindDir_AbvCnpy_6m,StdDev_WindDir_AbvCnpy_6m,TBRG_Rain,SnowDepth,SoilTemp_SWrod_2cm,SoilTemp_SWrod_5cm,SoilTemp_SWrod_10cm,SoilTemp_SWrod_20cm,SoilTemp_SWrod_50cm,SoilTemp_SWrod_100cm,SoilTemp_SErod_2cm,SoilTemp_SErod_5cm,SoilTemp_SErod_10cm,SoilTemp_SErod_20cm,SoilTemp_SErod_50cm,SoilTemp_SErod_100cm,SoilTemp_S_2cm,SoilTemp_S_5cm,SoilTemp_S_10cm,SoilTemp_E_2cm,SoilTemp_E_5cm,SoilTemp_E_10cm,SoilTemp_SW_2cm,SoilTemp_SW_5cm,SoilTemp_SW_10cm,SoilTemp_SE_2cm,SoilTemp_SE_5cm,SoilTemp_SE_10cm,SnowTemp_SW_1cm,SnowTemp_SW_2cm,SnowTemp_SW_5cm,SnowTemp_SW_10cm,SnowTemp_SW_20cm,SnowTemp_SW_30cm,SnowTemp_SW_40cm,SnowTemp_SW_50cm,SnowTemp_SE_1cm,SnowTemp_SE_2cm,SnowTemp_SE_5cm,SnowTemp_SE_10cm,SnowTemp_SE_20cm,SnowTemp_SE_30cm,SnowTemp_SE_40cm,SnowTemp_SE_50cm,CertificationCode,RevisionDate. (n/a),(n/a),(n/a),(UTC),(UTC),(UTC),(W/m2),(W/m2),(W/m2),(W/m2),(W/m2),(umol/m2/s),(umol/m2/s),(umol/m2/s),(umol/m2/s),(n/a),(degC),(degC),(degC),(degC),(%),(%),(m/s),(deg),(deg),(mm),(mm),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(degC),(n/a),(dymoyear) Met2,SK-HJP94,FlxTwr,2003,305,30,-52.6573,-1.5417,0.77405,224.125,274.466,0.18408,-0.1287,-999,-999,-999,-8.9164,-8.8968,-8.8026,-8.8774,61.018,61.742,3.3884,240.29,14.139,-999,204.44,-2.8073,-1.3517,0.14972,1.5077,4.2406,6.6301,-4.0818,-2.2276,-0.33036,1.086,3.598,6.2069,-3.1519,-1.1853,0.03288,-2.1463,-0.30172,0.60152,-2.6537,-0.86727,0.38026,-4.5593,-1.6673,-0.02878,-9.3051,-9.3683,-9.3112,-9.3038,-9.2467,-9.1889,-9.1849,-9.1395,-999,-9.6291,-9.73,-9.6221,-9.5121,-9.4883,-9.4281,-9.4633,PRE,14062004 Met2,SK-HJP94,FlxTwr,2003,305,100,-62.6021,-1.8274,0.90658,212.005,271.873,0.05983,-0.14274,-999,-999,-999,-9.5239,-9.3967,-9.332,-9.3939,63.108,63.79,3.1478,234.27,13.883,-999,204.51,-3.026,-1.481,0.10868,1.4886,4.2193,6.615,-4.4013,-2.442,-0.38369,1.0675,3.5759,6.1879,-3.517,-1.4897,0.03287,-2.3512,-0.34312,0.58471,-2.8503,-0.93888,0.36352,-4.9826,-1.8931,-0.06312,-10.026,-10.117,-10.04,-10.028,-9.9554,-9.8847-9.8702,-9.8072 -999,-10.479,-10.55,-10.391,-10.233,-10.207,-10.133,-10.165,PRE,14062004 8.4 Image Data [Describe the data submitted, with subsections 7.4.1 through 7.4.13 (below) being represented as columns in a tableExample: Identifier:OBS02031HH.PIX Date of Acquisition (UTC):31 January 2002 Time of Acquisition (UTC):16:13 Sensor / Mode:RADARSAT-1 SAR Standard Beam S1 Wavelength (nm) / Frequency (GHz):Standard Platform Altitude (magl):N/A Spatial Ground Resolution (m):30 Incidence Angle - Average:N/A Incidence Angle - Minimum:20.0 Incidence Angle - Maximum:27.4 Polarization:HH Gain Control:Automatic Flight Azimuth:Ascending Scene Centre:53.80206 N 104.61797 W 8.4.1 1 Image Identifier [A unique image file name that the image will be archived as, e.g. OBS02031HH.PIX.] 8.4.2 2 Date of Acquisition [As UTC.] 8.4.3 Time of Acquisition [Time as UTC; to allow later users to reproduce such things as sun angle.] 8.4.4 Sensor [Identify the imaging sensor and mode used.] 8.4.5 Wavelength [The wavelength range or frequency used. If settings are fixed, the descriptor "standard" can be used.] 8.4.6 Platform Altitude [The height of the sensor above the ground surface (m). If the altitude is fixed, such as for satellite platforms, N/A may be used.] 8.4.7 Ground Spatial Resolution [The smallest resolvable unit on the ground (m).] 8.4.8 .7 Incidence Angle - Average [The average angle from vertical.] 8.4.9 .8 Incidence Angle - Minimum [The minimum angle from vertical.] 8.4.10 Incidence Angle - Maximum [The maximum angle from vertical.] 8.4.11 Polarization [The polarization set on the sensor.] 8.4.12 Gain Control [Automatic or manual gain control.] 8.4.13 Flight Azimuth [Identify the direction of travel of the platform. For satellite-based platforms, Ascending or Descending is sufficient.] 8.4.14 Scene Centre [Give the scene centre in lat/long format.] --------------------------------------------------------------------------- 9 . Data Manipulations [This section describes the steps by which the data were processed to their final form.] 9.1 Post Processing and Calculated Variables [Specify all post-treatment of data, including data processing steps and calculations. Include relevant equations with definitions of terms and units.] Initially, data were recorded on a variety of loggers in various formats. Data from these loggers were brought into a common format and were organized by site, month and data type. Once data were organized into a common format, the first level of quality control was applied. This first stage of quality control included: - one-time "hard wired" fixes to resolve mistakes in data logger programming. - range and limit checking - application of calibration coefficients, and fixing of problems like incorrect wiring and conversion of units where required - manual exclusion of bad data where they could not be detected by automated range checking procedures - merging of manually quality controlled elements (including; Snow Depth) - and computation of derived or adjusted elements (including, Top-of-the-Atmosphere Shortwave Radiation, Downwelling and Upwelling Longwave Radiation Above Canopy, and Four Way Net Radiation Above Canopy.) This first stage of quality control was conducted automatically as part of the automated daily data retrieval. Once a week, the data were also plotted and inspected visually, using a graphical user interface that automated the plotting and data inspection processes. After the 1st stage of quality control it is intended that was some additional adjustments will be applied to these climate data in a second stage of QC, which are not yet in place, but likely will be. These will include: - correction of RH for a maximum value that exceeds 100% - correction of Shortwave_Rad and PAR for nighttime zero offsets - gap filling of some parameters where the estimates were judged to be highly accurate, e.g., the Longwave (PIR) data were analyzed to sort out the relationship between compensated and derived outputs, and then this relationship was used to fill gaps in the derived output. Again, the #rd dtage is also not yet in place but will include: filling data gaps in some key variables. Most data gaps will be filled using statistical relationships with related data from the same site or the other sites. These data files will not be available on the FC DIS, but will be available upon request (PI or data contact). 9.2 Special Corrections/Adjustments [List any 'special' corrections/adjustments made to portions but not all of the data to make it compatible with the data set as a whole.] The following are details on quality control procedures, stage 1. a) Limit checking and Range Checking This procedure sets out-of-limit data to missing. Two types of checks are performed, these include: - Rate-of-change checking; a maximum rate of change per time increment is set (i.e. air temperature must not exceed a rate of change per 30min period of 30 deg C, otherwise it will be set to missing). These values were purposely set high, so as not to exclude anything that might be real. - Limit Checking: each variable was assigned an absolute maximum and minimum value that recorded data was required to fall in to. Example: air temperature had to fall in between 45 and -50 deg C, otherwise it would be set to missing. These limits were also set high so that anything remotely real would not be excluded. Limit checking was used to flag questionable data but the data were not automatically excluded. b) Application of Calibration Coefficients and fixing of problems like incorrect wiring as well as conversion of units. Known corrections were listed in a separate file that was queried by the 1st level QC program. See "e) Derivation of new parameters" below for more information on these corrections. c) Merging of manually quality controlled elements Some elements were quality controlled manually, including cumulative precipitation and snow depth. If there were more than one element, they would be created in separate files and then merged into the main meteorological files at the first level of QC. Manual quality control of procedures are explained below: Snow Depth (non-gapfilled found in “Main” data files) ---------- The procedure for quality controlling snow depth in the Met2 files was partly manual and partly automated: - Snow depth in its raw form is recorded as the sensor height above ground, in mm. - First, the amount to subtract from the raw snow depth value to get actual snow depth was determined by manually browsing for a stable reference period of about one week before and after the snow season, where the instrument was “seeing” bare ground. - If this period was not manually found, then an automated procedure was in place do this, although typically it would not do as good a job as the human eye. o So far, it’s likely that this hasn’t happened yet. - In most cases, where the reference period did not change significantly over the snow season, one manual reference was used (usually a Fall measurement). - The snow depth was then calculated by subtracting the sensor measurement from the manual reference. - Example, the height of the sensor on Oct 31, 1998 was 2000mm and on April 15, 1999, it was 2000mm, therefore snow depth was computed by: (2000 - Distance from Sensor to Snow) = Actual Snow Depth - Ground truths, such as snow surveys and manual measurements of the height of the sensor above ground were also used to confirm/refute that the sensor was/was not working properly. Snow Depth (gapfilled – found in “MainGapfilled” data files) ---------- The procedure for quality controlling and gap filling snow depth in the Gap Filled files was as follows: - Any erratic summer data was cleaned up. - Some smoothing applied to noisy data o A filter called SGOLAY (in Matlab) was used to remove high frequency noise. The goal was to remove daily noise, which was usually the result of problems with the reference temperature required by the instrument to make its measurement. This filter works almost like a running mean. - Gaps were filled using a 5 day moving window linear regression. - If the height of the sensor changed significantly from what it was at the start of the season to what it was at the end of the season, a linear correction was applied. This correction was determined by computing the slope and intercept between the start and end times of the period in which the correction was to be applied. For example, if the height of the sensor on Oct 31 was 2000mm, but at the end of April, it was 1970mm, this type of correction was warranted. Manual snow depth measurements were also used to confirm that these linear corrections were justified. - Example: RawDepthPreSnow = Height of Sensor Above Ground on Last Snow Free Day = 1963mm RawDepthPostSnow = Height of Sensor Above Ground on 1st Snow Free Day = 2002mm TimePreSnow = Date of Last Snow Free Day = Nov 5, 2000 TimePostSnow = Date of 1st Snow Free Day = Apr 22, 2001 Slope = (TimePreSnow:RawDepthPreSnow,TimePostSnow:RawDepthPostSnow) Intercept = (TimePreSnow:RawDepthPreSnow,TimePostSnow:RawDepthPostSnow) Adjusted Snow Depth =(Slope*Time+Intercept-RawDepth) Manual Cumulative Precipitation ------------------------------- The procedure for accumulating Belfort Precipitation was a manual one. The procedure was quite simple (although a bit labour intensive): 1. If data was from a Belfort Universal (150mm) gauge, the 30 minute values were rounded off to the nearest 1/10th mm 2. If data was from a Belfort 3000 (500mm) gauge, the 30 minute values were rounded off to the nearest mm (note that the above steps may have already been done by the logger or an automated qc procedure) 3. Using the difference between 30 minute observations, a 30 minute accumulation was calculated for each 30 minute period. 4. The data was manually screened for gauge servicing (the dates of those were cross referenced with field notes when possible). 5. As a check, the difference between the last total weight before servicing and the last accumulated weight after the previous servicing was calculated. It was known that the Belfort gauges were usually accurate when it came to measuring the total weight in the bucket...this is what they do well. 6. The total of the 30 minute accumulations should have matched the difference in bucket contents as calculated above. However, it never did! 7. The observations were manually screened, one at a time, in order to distinguish between real and fictitious measurements. The most common error was rounding error computed by the datalogger. ie. A small change in the signal from the gauge may have alternated between a value of 100.64 mm (which = 100.6 mm) and 100.65 mm (which = 100.7 mm), resulting in 0.1 mm of false precip. These were systematically removed from the totals. For the most part, by eliminating these, the weights would match between servicings. Evaporation was another problem that made the weights mismatched. Eliminating this factor involved some judgment as to when evaporation occurred. It then had to be determined if the next positive weight increase was a result of the rounding problem or actual precipitation. The TBRG data helped in the summer but it was a judgment call in the winter. There were also instances where someone dumped fluid into the gauge. These false values also had to be removed. d) Derivation of new parameters from CNR1 radiometer (HJP94, HJP02, HJP75 and FEN): FourWayNet_Rad_AbvCnpy = CNR1_GlobalShortwave_Rad_AbvCnpy - CNR1_UpShortwave_Rad_AbvCnpy + CNR1_DownLongwave_Thermopile_AbvCnpy - CNR1_UpLongwave_Thermopile_AbvCnpy. Note that these variables have been corrected prior to deriving four way net radiation. DerivedUpLongwave_Rad_AbvCnpy = CNR1_UpLongwave_Thermopile_AbvCnpy+((5.67*10^-8)*(( CNR1_BodyPRT_Temp+273.15)^4)) DerivedDownLongwave_Rad_AbvCnpy = CNR1_DownLongwave_Thermopile_AbvCnpy+((5.67*10^8)*(( CNR1_BodyPRT_Temp+273.15)^4)) 9.3 Gap filling (applicable to files found in the “MainGapfilled” directory). A summary of gap filling procedures is given here. A more detailed document is available upon request from the PI. Operationally, gaps were filled one year at a time considering all possible related and available time series, however, only the variable that was most closely related to the missing variable was used to gap fill. Three different methods were used depending on the size of the gap and what variable needed to be filled. Here are the methods used: - Interpolated Difference o For this method, the difference between two similar variables was interpolated linearly. The difference between y and x were calculated for two points on either side of the missing section of data (when both were not missing). The difference was then estimated by linear interpolation for periods when y was missing and x was not. Gaps were then filled for y by adding the difference to x. - 5-Day Moving Window Linear Regression o This method used a linear regression to determine the relationship between the missing and non-missing variables. A flexible window of 240 (5d) non-missing data points, or 120 points, on either side of the missing section of data was used to determine this relationship and hence predict the missing section of data. - Moving Window Linear Regression, Same Time of Day o This method used a moving window, as in the 5-Day linear regression method above, except that the data were stratified by time of day (into 48 periods). A regression was done separately within each stratum, using a flexible window of 12 non-missing data pairs or 6 points (6 days) on either side of the section of missing data. Example: if data were missing at 1200 UTC, then a regression was calculated using data from 1200 UTC only, over a period of 6 days on either side of the missing section of data. Given below are the methods and variables used to gap fill, organized by variable type: - Global Shortwave Above Canopy o Moving Window Linear Regression Same Time of Day (forced through origin) for all gap sizes o Variables used to fill are either Global Shortwave or Downwelling PAR Above Canopy, however, if the gap couldn’t be filled by these two, then it’s possible that Upwelling Shortwave and Upwelling PAR were used. - Upwelling Shortwave Above Canopy o Moving Window Linear Regression Same Time of Day (forced through origin) for all gap sizes o Variables used to fill include Upwelling or Downwelling Shortwave or Upwelling or Downwelling PAR Above Canopy - Downwelling PAR (Above Canopy) o Moving Window Linear Regression Same Time of Day (forced through origin) o Variables used to fill are either Global Shortwave or Downwelling PAR Above Canopy, if the gap wasn’t filled by these two, then it’s possible that upwelling Shortwave and PAR were used. - Downwelling PAR (Below Canopy) o Moving Window Linear Regression Same Time of Day (forced through origin) o Any PAR variable could have been used - Upwelling PAR (Above Canopy) o Moving Window Linear Regression Same Time of Day (forced through origin) o Variables used: Downwelling or Upwelling PAR and Global Shortwave and Upwelling Shortwave (Above Canopy only for all). - Derived Downwelling Longwave Above Canopy o Interpolated Difference for small gaps (<24 periods, or 12h) and 5-Day Moving Window Linear Regression for large gaps (24 periods or more). o Variables used: Derived Downwelling Longwave, Derived Upwelling Longwave, Down or Upwelling Shortwave Above Canopy, Down or Upwelling PAR Above Canopy. - Derived Upwelling Longwave Above Canopy o Interpolated Difference for small gaps (<24 periods, or 12h) and 5-Day Moving Window Linear Regression for large gaps (24 periods or more). o Variables used: Derived Downwelling Longwave, Derived Upwelling Longwave, Down or Upwelling Shortwave Above Canopy, Down or Upwelling PAR Above Canopy. - 4-Way Computed Net Radiation Above Canopy. If any gaps existed in the gap filled data, it would have been due to one of the 4 components being missing. First, gaps were filled in the components that were missing and then the 4-Way was re-computed. - Net Radiation Above Canopy o Moving Window Linear Regression Same Time of Day o Variables Used: Net Radiation Above Canopy (also included the 4-Way Computed Net Radiation) and Downwelling or Upwelling Shortwave Above Canopy. - Air Temperature (any height, any type of measurement) o Interpolated Difference for small gaps and Moving Window Linear Regression Same Time of Day for large gaps. o Variables Used: Air Temperatures, Shallow (<=20cm depth) Soil Temperatures and Tree Temperatures (any level or location). - Shallow Soil Temperature (<=20cm depth) o Interpolated Difference for small gaps and Moving Window Linear Regression Same Time of Day for large gaps. o Variables Used: Air Temperatures, Soil Temperatures and Tree Temperatures (any level or location). - Tree Temperatures (any location or tree depth) o Interpolated Difference for small gaps and Moving Window Linear Regression Same Time of Day for large gaps. o Variables Used: Air Temperatures, Shallow (<=20cm depth) Soil Temperatures and Tree Temperatures (any level or location). - Deep Soil Temperature (50cm and 100cm depth) o Interpolated Difference for all gap sizes. o Variables Used: All Soil Temperatures (any depth). - Relative Humidity (any height) o Interpolated Difference for small gaps and Moving Window Linear Regression Same Time of Day for large gaps o Only RH used to fill gaps. - Soil Heat Flux (any location or depth) o Interpolated Difference for small gaps and Moving Window Linear Regression Same Time of Day for large gaps o Only Soil Heat Flux used to fill gaps. - Wind Speed (any location or height) o Interpolated Difference used for small gaps and 5-Day Moving Window Linear Regression for large gaps. o Only Wind Speed used to fill gaps. - Atmospheric Pressure o Interpolated Difference used for small gaps and 5-Day Moving Window Linear Regression for large gaps. o Only Atmospheric Pressure used to fill gaps. --------------------------------------------------------------------------- 10 . Errors and Limitations [This section describes an error analysis for the data.] 10.1 Sources of Error [Describe what factors of the instrument or environment may introduce errors in the observations.] See section on "Known Problems with the Data" for more information. 10.2 Quality Assessment 10.2.1 Data Validation by Source [Describe all efforts to validate the data by the submitter, e.g. comparisons with data from other investigators.] Data were quality assured by comparing simiar variables at the same site and also by comparing variables at different sites within the BERMS area. This was done weekly, in near real time, to ensure that problems were flagged and fixed in a timely manner. 10.2.2 Confidence Level/Accuracy Judgment [Subjective discussion of data quality.] The data submitted are of good quality with minimal amount of errors. However, any measurement is not perfect, and the user must be aware of the limitations of the instrumentation. 10.2.3 Measurement Error for Parameters [Quantitative error estimates.] See section on Equipment for more instrument specs. 10.2.4 Additional Quality Assessments [May include visual review of plots, etc.] 10.3 . Limitations and Representativeness [Provide warnings on the use of the data, e.g. data were collected under drought conditions relations between variables may be different when things are wet, as well as known problems. Discuss how representative your data is, eg: of the landscape, climate, footprint, etc.] See section on Known Problems below for more information. 10.4 Known Problems with the Data Problems to be aware of at all Saskatchewan BERMS sites: - Beware that there was an unusual amount of frost build-up, particularly on the radiation sensors, during the winter of 1997/98. Frost problems have occurred in other years, but not to the same extent. Frost can either cause a drop or an increase in radiation measurements depending on the sensor. Frost can also cause the propellers on wind instruments to seize up and not record wind speeds above 0 m/s. - Non-zero shortwave and PAR at night during some periods: some possible causes of this include poor wiring and/or stray voltages from the ventilation fan. - Specific problems have been listed in the file: QC_Notes.txt/xls. - Relative humidity measured by Vaisala HMPs often drift above 100%. Nothing has been done to correct this problem at the first stage of QC. Higher level QCd files, which will be available at a later date will make adjustments to RH, particularly for values near and above 100%. - Some Vaisala HMP temperatures would often go missing for the one 30min period in which phone downloads took place. This problem remained unresolved. Data problems at H02: - 2003 July: Power outage due to tornado in area affects H02 as well as other sites. - 2003: Site experiences communication problems intermittently. - 2003 and 2004: Problems with PAR, ALbedo and transmittence occur intermittently throughout 2003 and 2004. - 2004: Some soil Temp and heat flux measurment bad or missing. - 2005: Soil temp missing intermittently. - 2007 June 6 to 2009 July 8: Thermocouple Temp at 2m is bad and has been excluded. The ventilator the sensor was housed in was not working properly and was affecting the data quality (temp was too high due to burned out fan). - 2007 June 6 to 2008 January 17: HMP Air Temp at 2m has been excluded for the same reason as above (this sensor is housed in same ventilator). This sensor was removed from the ventilator temporarily when the problem was discovered. - 2008 June 21 to August 21: All precipitation data, Windspeed at the Geonor Precip Gauge and atmospheric pressure is missing due to instrument failure. Data gaps have been manually filled for the Geonor precip gauge. - 2008 July 11 to October 7: Major problems with power supply and instrumentation. Soil temps all depths at E, NE and W pit, as well as soil heat flux W, E and SurfaceDebris, are missing during this period. - 2009 January to October: Downwelling PAR at 3m showing a significant nighttime offset (up to +40W/m2). This problem is likely related to water leaking in to the wiring. - 2009 February 26 (DOY 057) at 16:00 UTC to May 26 (DOY 146) at 20:00 UTC: VWC is missing due to a power supply problem. --------------------------------------------------------------------------- 11 . Software 11.1 Software Description [Describe all software that was used to process the data.] Various kinds of plotting and housekeeping software were used to view and process BERMS meteorology data. Some software was commercially available (like PC208 from Campbell Scientific), while others were programs written in C++ and Matlab. Here is a list of current programs and their functions: *** To be written *** 11.2 Software Access [Describe any software that may be available for use by someone who may want to perform further processing of the data. Also describe where a user can get it -- commercial source, Web site, FTP archive, e-mail to author, etc.] Please feel free to contact the following people to discuss software availability and usage: Steve Enns Phone: (306) 975-5683 Email: Steve.Enns@ec.gc.ca Alan Barr Phone: (306) 975-4324 Email: Alan.Barr@ec.gc.ca --------------------------------------------------------------------------- 12 . References 12.1 Platform/Sensor/Instrument/Data Processing Documentation [List any published documentation relevant to the data collected, such as manufacturer's instruction manuals, government technical manuals, user's guides, etc.] Belfort Instrument Company. 1986. Instruction Manual Catalog Number 5-780 Series Universal Recording Rain Gage, Instruction Manual number 8777. Campbell Scientific. 1983. Model 207 Temperature and Relative Humidity Probe Instruction Manual. Campbell Scientific. 1990. SBP270 Barometric Pressure Sensor Instruction Manual. Campbell Scientific Canada Corp. Campbell Scientific. 1992. UDG01 Ultrasonic Depth Gauge Operator?s Manual. Campbell Scientific Canada Corp. Campbell Scientific. 1992. Model HMP35CF Temperature and Relative Humidity Probe Instruction Manual. Campbell Scientific. 1993. CR7 Measurement and Control System Instruction Manual. Campbell Scientific Inc. Campbell Scientific. 1996. CS615 Water Content Reflectometer Instruction Manual. Campbell Scientific Inc. Campbell Scientific. May, 1998. Model HMP45C Temperature and Relative Humidity Probe Instruction Manual. Campbell Scientific Corp. Campbell Scientific. Sept, 1998. SR50 Sonic Ranging Sensor Operator's Manual. Campbell Scientific Corp. Carter-Scott Design. No Date. Middleton CN3 Heat Flux Plate Application Note. Carter-Scott Design. May 1995. Instruction Manual for Middleton CN1-R Net Pyrradiometer Edition: CN1R-v1.1. Druck Incorporated. No Date. PTX Depth Pressure Transmitter, Installation and Application Notes. EPLAB, The Eppley Laboratory, Inc. No Date. Instruction Sheet for the Eppley Precision Radiometer (Model PIR). ESI Environmental Sensors Inc. No Date. Moisture Point Instruction Manual. Geonor T-200 Precipitation Sensors. 1995. Instruction Manual Gray, D.M. 1981. Handbook of Snow. Toronto, ON: Pergamon. Hukseflux Thermal Sensors. 2000. instruction Manual. Kipp and Zonen. No Date. Instruction Manual Pyranometer CM 11/14. LI-COR. 1991. LI-COR Radiation Sensors Instruction Manual. NASA. 1994. BOREAS Experimental Plan, Version 3. Phillips, D. 1990. The climates of Canada. Ottawa: Canadian Government Publishing Centre. R.M. Young Company. 1980. Instructions, Gill Microvane 3 Cup Anemometer. R.M. Young Co. R.M. Young Company. 1990. Wind Monitor High Resolution Wind Sensor information sheet. R.M. Young Co. Environment Canada. 1993. Canadian Climate Normals 1961-90. Wheaton, E. 1998. But It?s a Dry Cold!. Calgary: Fifth House Ltd 12.2 Journal Articles and Study Reports [List technical reports and scientific publications that concern the methods, instruments, or data described in this document. Publications by the Principal Investigator or investigating group that would help a reader understand or analyze the data are particularly important.] Arain, M.A., T.A. Black, A.G. Barr, P.G. Jarvis, J.M. Massheder, D.L. Verseghy, and Z Nesic. 2002. Effects of seasonal and interannual climate variability on net ecosystem productivity of boreal deciduous and conifer forests. Can. J. For. Res. 32: 878-891. [Abstract] Blanken, P.D., T.A. Black, H. H. Neumann, G. den Hartog, P. C. Yang, Z. Nesic and X. Lee. 2001. The seasonal water and energy exchange above and wthin a boreal aspen forest. Journal of Hydrology. 245(1-4): 118-136. [Abstract] Barr, Alan G., G. van der Kamp, R. Schmidt and T.A. Black. 2000. Monitoring the moisture balance of a boreal aspen forest using a deep groundwater piezometer, Agric. For. Meteorol. 102:13-24. [Abstract] Black, T.A., W.J. Chen, A.G. Barr, Z. Chen, M.A. Arain, Z. Nesic, E.H. Hogg, H.H. Neumann and P.C. Yang. 2000. Increased carbon sequestration by a boreal deciduous forest in years with a warm spring. Geophys. Res. Letters. 29(9): 1471-1274. Chen, W., Black, T.A., Yang, P., Barr, A.G., Neumann, H.H., Nesic, Z., Novak, M.D., Eley, J., Ketler, R., and Cuenca, C. 1999. Effects of Climatic Variability on the Annual Carbon Sequestration by a Boreal Aspen Forest. Global Change Biology, 5(1): 41-53. [Abstract] --------------------------------------------------------------------------- 13. Glossary of Terms and Acronyms [Define discipline-related jargon and the wealth of scientific notations/symbols that may be used in the text, as well all "local" acronyms. Items from the following list may be included. BERMS - Boreal Ecosystem Research and Monitoring Sites BOREAS - BOReal Ecosystem-Atmosphere Study PANP - Prince Albert National Park FCDIS - Fluxnet-Canada Data Information System MSC - Meteorological Service of Canada (a branch of Environment Canada) BERMS - Boreal Ecosystem Research and Monitoring Sites BOREAS - Boreal Ecosystem-Atmosphere Study BORIS - BOREAS Information System NHRC - National Hydrology Research Centre NWRI - National Water Research Institute SRC - Saskatchewan Research Council UTC - Universal Coordinated Time --------------------------------------------------------------------------- 14 . Document Information 14.1 Document Revision Date [Use yyyy-mm-dd-mmm format] 2005-03-21 2004-12-21 2004-03-22 2003-09-29 14.2 Document Author Charmaine Hrynkiw, Kim Kovacs 14.3 Keywords [Include a list of appropriate key words to assist in searching for information.] Meteorology, climate, jack pine, southern boreal forest, harvested jack pine