SGP97 DOE ARM SGP EBBR Data 1.0 General Description The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Energy Balance Bowen Ratio (EBBR) is one of various data sets provided for the Southern Great Plains 1997 (SGP97) project. This data set contains 30 min averages of net radiation, atmospheric pressure, soil moisture (at five locations surrounding the sites), soil temperature (at five locations surrounding the sites), soil heat flow (at five locations surrounding the sites), corrected soil heat flow (at five locations surrounding the sites), soil heat capacity (at five locations surrounding the sites), change in energy storage (at five locations surrounding the sites), soil heat flow at the surface (at five locations surrounding the sites), average soil heat flow at the surface, bowen ratio, latent heat flux, sensible heat flux, scalar wind speed, resultant wind speed and wind direction from 12 locations at the ARM SGP site. This data set covers the period from 1 June through 31 July 1997. The SGP97 domain is approximately 97W to 99W longitude and 34.5N to 37N latitude. No additional quality control was performed by the University Corporation for Atmospheric Research/Joint Office for Science Support (JOSS). These data are in their original NetCDF format. 2.0 Note of this Documentation File The remainder of this document comes from the ARM program. An up-to-date version of this document (including figures mentioned within the text) is available on the WWW at: http://www.arm.gov/docs/instruments/static/ebbr.html 3.0 General Purpose The Energy Balance Bowen Ratio (EBBR) system is a ground-based system using in situ sensors to estimate the vertical fluxes of sensible and latent heat at the local surface. EBBR systems will be installed at up to 15 grassland locations within the SGP CART Site. Flux estimates are made from observations of net radiation, soil heat flow, and the vertical gradients of temperature and relative humidity; these data are used in the Bowen ratio energy balance technique. 4.0 Primary Quantities Measured with System The primary quantities measured are 30-minute averages of the energy flux densities (watts per meter squared) of sensible and latent heat, representative of the grassy area within about 50 meters of the EBBR station. Secondary quantities include air temperature, reference temperature, relative humidity, net radiation, near-surface soil moisture, near-surface soil heat flux, near-surface soil temperature, atmospheric barometric pressure, wind direction, wind speed, and battery voltage. These secondary quantities are not designed to be used as primary quantities for the purposes of SGP CART meteorological or radiation measurements and therefore should be used with caution for that purpose. Instead, the corresponding primary meteorological quantities from co-located systems (if available) should be used. Systems from which primary meteorological quantities are available include the SMOS. Units and heights (or depths) of secondary quantities vary (units vary depending on averaging time); see Examples of Data and Description of System Configuration and Measurement Methods. 5.0 Detailed Description 5.1 List of Components The accuracies cited below are generally those stated by the manufacturer. They are sensor absolute accuracies and do not include the effects of system (i.e., datalogger) accuracies. Although it is not known how some of the manufacturers have determined sensor accuracy, it is properly the root square sum of any nonlinearity, hysteresis, and nonrepeatablity, usually referenced as percentage of full scale. The detection limit is normally restricted to the range (sometimes called Calibrated Operating Range) over which the accuracy applies. In the case of the EBBR, some of the detection limits are those determined by the vendor (REBS) who performed the calibration, not by the manufacturer of the sensor. Some manufacturers also specify an Operating Temperature Range in which the sensor will physically and electronically function, even though the calibration may not be appropriate for use throughout that range. When no detection limits have been listed by the manufacturer or the calibrating vendor, none are stated below. Air temperature: Chromel-constantan thermocouple, Omega Engineering Inc., REBS Model # ATP-1, Detection Limits -30 to 40 deg C, Accuracy +/- 0.5 deg C. Temperature/Relative Humidity Probe: Operating Temperature Range -20 to 60 deg C. Temperature: Platinum Resistance Temperature Detector (PRTD); Detection Limits -30 to 40 deg C, Accuracy +/- 0.2 deg C Relative Humidity: Capacitive element, Vaisala Inc., Model #s HMP 35A and HMP 35D; Detection Limits 0% to 100% RH, Accuracy +/- 2% (0-90% RH), +/- 3% (90-100%), uncertainty of RH calibration +/- 1.2%. Soil Temperature: Platinum Resistance Temperature Detector, MINCO Products, Inc., REBS Model # STP-1, MINCO Model # XS11PA40T260X36(D), Detection Limits -30 to 40 deg C, Accuracy +/- 0.5 deg C. Soil Moisture: Soil Moisture Probe (fiberglass and stainless steel screen mesh sandwich), Soiltest, Inc., REBS Model # SMP-2, Soiltest Model # MC-300, Accuracy not specified by manufacturer (varies significantly depending on soil moisture and soil type). Detection limits for this sensor are limited by the ability to fit a polynomial to the calibration data; for the SGP CART Site the detection limits are approximately 1% to 50% by volume. Soil Heat Flow: Soil Heat Flow Probes, Radiation & Energy Balance Systems, Inc., Model #s HFT-3, HFT3.1, Accuracy not specified by manufacturer. Barometric Pressure: Barometric Pressure Sensor, Met One Instruments, Model #s 090C-24/30-1, Detection Limits 24 to 30 kPa; 090C-26/32-1, Detection Limits 26 to 32 kPa; 090D-26/32-1, Detection Limits 26 to 32 kPa; Accuracy for all +/- 0.14 kPa. Net Radiation: Net Radiometer, Radiation & Energy Balance Systems, Inc., Model Q*6.1 or Q*7.1, Accuracy +/- 5% of full-scale reading. Wind Direction: Wind Direction Sensor, Met One Instruments, Model #s 5470, 020C, Detection Limits 0 to 360 deg physical (for greater than 0.3 ms-1 wind speed), 0 to 356 deg electrical, Accuracy +/- 3 deg. Wind Speed: Wind Speed Sensor, Met One Instruments, model #s 010B and 010C, Operating Temperature Range -50 to 85 deg C, Detection Limits 0.27 to 50 ms-1, Accuracy +/- 1% of reading. Operational Limit on speed 60 ms-1. Datalogger: Campbell Scientific, Inc., Model CR10, Detection Limits vary by voltage range selected, Accuracy +/- 0.1% of full scale reading. 5.2 Description of System Configuration and Measurement Methods The meteorological observations made with the EBBR system are: Air temperature at two heights (1 m separation) Relative humidity at two heights (1 m separation) Net radiation (at 2 m typical) Soil moisture at 2.5 cm depth Soil heat flow at 5 cm depth Soil temperature, integrated 0 to 5 cm Barometric pressure Wind direction at 2.5 m Wind speed at 2.5 m Reference temperature of control box The EBBR sensors (except for soil probes) are mounted on a triangular pipe framework that sits on the soil surface. The net radiometer mount extends from the south end of the EBBR frame. A unique aspect of the system is the automatic exchange mechanism (AEM), which helps to reduce errors from instrument offset drift. The AEM extends from the north end of the frame. Aspirated radiation shields (which house the air temperature and relative humidity probes) are attached to the AEM. The openings of the aspirated radiation shields face north to reduce radiation error from direct sunlight. The soil probes are buried just outside the view of and in an arc to the south of the net radiometer. Heights of individual sensors are listed in Primary Quantities Measured with System. Heights of air temperature and relative humidity sensors vary from site to site and are dependent on vegetation height; these heights can vary seasonally as vegetation height changes. The reference temperature sensor, barometric pressure sensor, datalogger, storage module, and communication equipment are located in the control box, which is attached at the northeast corner of the EBBR frame. The local area of influence upon Bowen ratio measurements is contained within a horizontal distance of approximately 20 times the height of the top aspirated radiation shield on the AEM. This distance varies among the different extended facilities and for different times of the year because of differences in vegetation height, and therefore the height at which the AEM is installed. The manufacturer's (REBS) name for these systems is SEBS (Surface Energy Balance System) ; this is the name that appears in their systems documentation. Methods of measurements are further described under Theory of Operation and under Frequently Asked Questions (FAQs). 5.3 Assessment of System Uncertainties for Primary Quantities Measured The EBBR system is capable of producing estimates of 30-minute average sensible and latent heat fluxes accurate to approximately +/- 10% of the estimated value or +/- 10 watts per meter squared, whichever is larger, at the 95% confidence level. Offset and calibration drift errors in the measurements of the temperature and relative humidity gradients are significantly reduced by the use of the AEM, which switches the positions of the upper and lower sensors every 15 minutes. There are a number of conditions under which the primary quantities may be incorrect. The data user should examine the data quality flags (described in Explanation of Flags Applied During Data Ingest) and data quality reports (DQR) to determine whether significant malfunctions have occurred in the EBBR system. The more frequent sources of error are described briefly here. See 6. under Frequently Asked Questions (FAQs) for information on errors produced by improper operation of the AEM. Generally, when the AEM is not functioning properly, the sensible and latent heat flux estimates are unreliable and should not be used. Examine the data quality flags for AEM home signals to ensure that only flux data produced when the AEM is functioning properly is used. Another source of error in the sensible and latent heat flux estimates lies in net radiation measurement errors. An error in the net radiation results in the same percentage error in the heat flux estimates. Condensation or frost sometimes forms on the upper net radiometer dome (called a "windshield" by the manufacturer) at night, especially when the relative humidity is high, wind speeds are very low, and the sky is clear (allowing rapid radiational cooling). This can persist until early afternoon, especially on the side of the net radiometer that is away from the sun. If the net radiometer dessicant is not in good condition, condensation can also occur inside the dome during the nighttime and can persist until early afternoon. Dessicant in poor condition can desorb water vapor into the dome area during the nighttime portion of the natural diurnal "breathing" process through the dessicant; some air passes through the dessicant and into the domes as the ambient temperature decreases with the approach of nightfall. Conversely, in the morning, the air in the domes warms and some moves through the dessicant in the opposite direction, thereby reducing the water vapor content of the air. This "breathing" process is intended to keep the air inside the domes dry. Condensation or frost inside or outside the domes can cause a decrease in net radiation to be measured during the day and an increase at night. During the day, the condensation or frost obstructs the passage of solar and infrared radiation through the top dome, thereby causing too low a value to be measured. At night, the condensation or frost prevents the cooling of the upper sensing surface of the net radiometer, thereby resulting in too large a net radiation value. The nighttime error in net radiation has, in extreme conditions, been measured to be as much as 30 watts per meter squared. Within a year of installation of the first EBBR systems it was obvious that the dessicant was degrading and had to be replaced more frequently than should have occurred. The cause was found to be a poor seal of the domes and the sensor head, a result of a poor sealing design. During the nighttime, undessicated ambient air would leak into the dome area around the seals. The manufacturer subsequently modified the design, resulting in fewer occurrences. Furthermore, a procedure to test the seal on the domes every 3 months and at each dome change was instituted. The polyethylene domes (particularly the upper one) degrade (become cloudy) from exposure to sunlight, most rapidly in the first several months of use. After 6 months, the degradation may result in as much as a -5% error in net radiation during the day, but with a negligible error at night. The domes are scheduled to be replaced every 3 months to minimize this error. At first, the spare domes obtained from the manufacturer appeared to vary significantly in thickness, a possible small source of error (within the accuracy stated by the manufacturer). The nature of the manufacturing process (forming polyethylene hemispheres from a sheet of material) lends itself to some variation in thickness of the final product. The manufacturer was subsequently asked by ARM to inspect future domes for abnormalities before they are sent to the SGP CART Site. The net radiation measurement is also affected by the amount of cooling produced by wind speeds of various magnitudes. The cooling effect is greatest on the top portion of the net radiometer (whose surface is warmest during the day because of solar radiational heating), primarily during daylight hours. After April 1996, a correction to net radiation, based on wind speed, was included in the CR10 software used in each EBBR calibration changeout kit. The changeouts were completed in November 1996. In 1997, specially designed ventilators are to be added to the net radiometers. The ventilators provide a non-wind-dependent airflow, the effect of which is easily included in the CR10 programming. This constant airflow will reduce the number of occurrences of condensation and frost on the net radiometer domes, thereby reducing the amount of incorrect net radiation data at night and in the morning. The data user may also compute the net radiation as a sum of the solar and infrared components measured by a co-located SIRS station, to help identify when EBBR net radiometer problems may occur. A quality measurement experiment (QME) makes this evaluation routinely. Furthermore, an error occurs when the Bowen ratio has a value near -1. An example of the "spike" that can occur in the heat fluxes is seen in the figure in Examples of Data. To address this difficulty, use of a bulk aerodynamic (BA) approach in a QME has been proposed to produce an alternative data stream where EBBR heat flux data is replaced with BA results when the Bowen ratio value is between -0.75 and -1.5. At present, a data quality flag for this condition has not been implemented, mostly because of the plethora of messages that would appear in the Site Operations Log as a result. Another source of error can be possible inaccuracies of the soil measurements (soil temperature change with time, soil moisture, soil heat flow at 5 cm) used to calculate estimated soil heat flux; aging of the sensors with time can result in changes in calibration or offset. When such changes become significant, the standard procedure is to replace the sensor and submit a DQR indicating the amount of error involved. Rarely is the error sufficiently large to declare the sensible and latent heat fluxes incorrect. The soil heat flux is normally a small fraction of the total energy exchange at the surface. Inaccuracies in the soil heat flux estimates normally cause less than a +/- 5% error in the sensible and latent heat fluxes. However, a total failure of a soil sensor (this is always reported in a DQR) often requires that the sensible and latent heat fluxes be recalculated using soil heat flux determined from the functioning sets of soil sensors only. The information needed to perform the recalculation is provided in the DQR. The alternative is to not use the sensible and latent heat flux estimates when a DQR has reported a soil sensor failure. One condition that may be hard for the data user to detect involves the failure of one of the air temperature thermocouples from which temperature gradient is determined. A failed thermocouple will typically result in offscale top and bottom air temperatures, thereby producing a zero temperature gradient and no sensible heat flux. The latent heat flux that is reported is then incorrect. It is possible for the sensible and latent heat fluxes to be recalculated using the relative humidity probe temperatures in place of the thermocouple temperatures; this method may add a small amount of error to the resulting fluxes, but should produce fluxes that are within 20% of those that would have been calculated using the thermocouples. Another condition that needs to be "looked out for" is rapid changes in net radiation. Rapid changes during the basic measurement averaging time of 12 minutes per quarter hour can result in non-linear changes that the 30 second sampling interval does not handle well; in other words, the average of one or all of net radiation, temperature gradient, and vapor pressure gradient do not reflect a correct average of the rapid changes; this is a result of undersampling. Normally, this condition is difficult to distinguish from normal variations, but on occasion it has been pronounced, even causing an unexpected sign of one heat flux (usually sensible) and a very large value for the other (usually latent). This condition most commonly occurs with saturated soil and partly cloudy conditions. 5.4 Description of Observational Specifications The EBBR is a multi-sensor system and, therefore, the measurement capability of the system is limited by the accuracies and detection limits of individual sensors and the resolution of the data logger. The quality control limits used in the data ingest module generally exceed the manufacturer's stated detection limits. See the section List of Components for details on sensor detection limits, accuracies, and operating limits. Ultimately, the range of measurement is restricted to the ranges of analog voltage supported by the datalogger. None of the sensor ranges exceeds the ability of the Campbell CR10 datalogger to measure them. The range of primary quantities (sensible and latent heat flux density) that the EBBR system is capable of measuring is much greater than the expected natural range of heat fluxes for the SGP CART Site (approximately -700 to 100 watts per meter squared). 6.0 Theory of Operations The EBBR stations use a standard approach that has been described by textbooks and articles. A general description can be found in the book titled Evaporation in the Atmosphere by W. H. Brutsaert (D. Reidel Publishing Company, Dordrecht, Holland, 1982, pp. 210-212). For a recent article, see p. 18,549 of the special FIFE issue of the Journal of Geophysical Research (Vol. 97, pp. 18,343-19,110). The surface energy balance equation is used: Rn + G + H + LE = 0, where Rn is net radiation, G is the ground heat flux measured as described later, H is sensible heat flux, and LE is latent heat flux. The units for the terms in this equation are watts per square meter. H and LE are not measured directly but are inferred from the gradients of temperature and relative humidity across two fixed heights within 3 meters of the surface. The Bowen ratio (B = H/LE) is computed on the basis of the gradients and the following computations are performed: LE = -(Rn + G)/(1 + B) H = B LE More detailed information on these and other equations can be obtained elsewhere, including from David Cook and Marv Wesely at Argonne National laboratory. For example, a large manual provided the manufacturer, REBS, Inc., describes the general theory, gives rather complete information on each type of sensor, and explains procedures for installation, operation, and maintenance. 7.0 ARM Data Quality Reports 7.1 E8 Incorrect Soil Temperature #s 1 and 2 Platform/Measurement: What location was the data collected at: E8, Coldwater, KS Period of time in question Begin Date 08/03/96 Time 0000 GMT End Date 06/10/97 Time 2200 GMT Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: Soil temperature probes #1 and #2 went offscale at times for many months. Replacement probes were not available until recently. The probes were replaced on 16 June, 1997 at 2200 GMT. Affected data values were: 30 minute: sm2, ts2, c_shf2, ces2, cs2, g2, ave_shf, e, h Suggested Corrections of the Problem: (e.g. change calibration factor and recompute, flag data with this comment, etc.) Flag data with these comments. 7.2 Soil Moisture Sensor Offscale Platform/Measurement: EBBR/Soil Moisture What location was the data collected at: E4, Plevna, OK Period of time in question Begin Date 03/10/1997 Time 0830 GMT End Date 06/11/1997 Time 2000 GMT Data should be labeled: _x_ incorrect _X_ Only some data fields affected Discussion of Problem: The 30 minute output of soil moisture sensor #5 at Plevna, Ok, E4 has been going to a large magnitude negative number for low soil moistures for several months. The calibration coefficients were inadequate for low soil moistures. The coefficients have been changed to yield correct soil moistures at low soil moisture (at least, manipulation of the polynomial for low soil moistures yields correct results for a fixed temperature correction - extremes of soil temperature and thus the correction may not yield as satisfying results). These coefficients were derived from the original calibration data, but including use of low values not used originally. This particular probe's calibration data was almost exactly the same as another probe used at the same site, yet the coefficients derived by the vendor were very different. This made it particularly obvious that the original coefficients were not adequately tested (verification tests are not normally performed with dry soil, so this kind of problem would not normally show up during verification tests). Several days of data using the new coefficients yields encouraging results. I will continue to inspect the data to determine the success of this change. Data values affected: 30 minute: sm1, ave_shf, g1, c_shf1, cs1, ces1, h, e Suggested Corrections of the Problem: (e.g. change calibration factor and recompute, flag data with this comment, etc.) Flag data with this comment if possible. 7.3 E9 EBBR Temperature Portion of T/RH Probe Platform/Measurement: EBBR/Soil Heat Flow What location was the data collected at: E9, Ashton, KS Period of time in question Portions of: Begin Date 7/15/96 1715 GMT End Date 6/18/97 1645 GMT Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: The Temperature portion of the right T/RH probe indicated too high a temperature for nearly 11 months. I twice placed work requests to have the probe replaced, but no spares were available. Spares recently became available and I placed a new work request to have the probe changed. The replacement occurred on 18 June 1997; this fixed the problem. The main results of the high temperatures were probe top and bottom temperatures (used only for the calculation of vapor pressure) and vapor pressures that were too large. Furthermore, this caused latent heat flux to be reported to be too large, and therefore sensible heat flux was reported to be too small. Recalculation of the fluxes using thermocouple temperatures to calculate vapor pressure would be quite time consuming and would have to assume that the thermocouple temperature and probe temperature were nearly the same. The EBBR procedures have been changed to include comparison of the thermocouple and probe temperatures to make it easier for the site operators to detect this condition. The data affected (and thus incorrect) includes: 30 minute: thum_top, thum_bot, vp_top, vp_bot, e, h, bowen. Suggested Corrections of the Problem: (e.g. change calibration factor and recompute, flag data with this comment, etc.) Flag with this comment. 7.4 E26 Soil Heat Flow Sensor 1 Replacement Platform/Measurement: EBBR/Soil Heat Flow Sensor #4 What location was the data collected at: E26, Cement, OK Period of time in question Begin Date 12/03/96 1930 GMT End Date 06/17/97 2030 GMT Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: Apparently, during installation of the present system on 17 July 1996, soil heat flow sensor #4 was intentionally placed upside down in the soil to produce the correct sign of flux. The leads from the sensor must have been connected with the wrong polarity. On 3 December 1996 site operations corrected some wiring problems and reconnected soil heat flow sensor #4 according to the proper color code; this caused the sign of the soil heat flow from that sensor to then be opposite of the other four sensors. All data from sensor #4 is the wrong sign during the period listed above. On 17 June 1997 site operations removed the sensor and installed it with the correct side up, fixing the problem. The result of this problem was a decrease of reported average soil heat flow of approximately 40%. This translates into a 0 to 20% error in latent and sensible heat fluxes (soil heat flow is rarely more than 50% of net radiation, upon which the Bowen ratio calculation depends). Therefore, sensible and latent heat fluxes were typically overestimated by about 10% during the daytime. This is of the same magnitude as the EBBR system/technique error. The following data values were affected for the period listed above: 30 minute: shf4, c_shf4, g4, ave_shf, e, h The latent and sensible heat fluxes can be recalculated by using only soil heat flows 1, 2, 3, and 5 to calculate the average soil heat flow, ave_shf = (g1 + g2 + g3 + g5)/4 e = -(q + ave_shf)/(1 + bowen) h = -(e + ave_shf + q). Suggested Corrections of the Problem: (e.g. change calibration factor and recompute, flag data with this comment, etc.) Flag with this comment. 7.5 E8 Incorrect Soil Temperature #s 1 and 2 Platform/Measurement: What location was the data collected at: E8, Coldwater, KS Period of time in question Begin Date 06/15/97 Time 1500 GMT End Date 06/24/97 Time 2000 GMT Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: Soil temperature probes #1 and #2 were replaced on June 10, 1997. However, the leads were apparently not connected tightly enough, resulting in some large or offscale resistance measurements and therefore temperature values for those probes. The problem occurred only occasionally until June 20, 1997. On June 20 - 24, 1997 probes 1 and 2 outputs were offscale for several hours per day, both not always at the same time. On June 24, 1997, site operations checked and tightened the connections. No offscale values have occurred since then. Affected data values were: 30 minute: sm2, ts2, c_shf2, ces2, cs2, g2, ave_shf, e, h Suggested Corrections of the Problem: (e.g. change calibration factor and recompute, flag data with this comment, etc.) Flag data with these comments. 7.6 E8 EBBR AEM Inoperative Platform/Measurement: EBBR/AEM What location was the data collected at: E8, Coldwater, KS Period of time in question Begin Date 06/19/97 0130 GMT End Date 07/08/97 1915 GMT Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: Beginning on 19 June 1997, the set screw holding one of the AEM sprockets to the drive motor became stripped, preventing the aspirator units from exchanging every time. The problem was intermittent until 24 June when site operations personnel determined that a new sprocket (therefore a replacement AEM) was needed. The AEM was therefore left in the position such that the right aspirator was in the bottom position continuously, with home signals indicating values near -1. The AEM was replaced on 8 July 1997. For most of the time period above, home signals, bowen, e, h, and all thermocouple and probe tmperatures, probe relative humidities, and vapor pressures do not reflect a switching AEM. However, temperatures, RH and vapor pressures are accurate for their height. Obviously, bowen, e, and h are incorrect. Suggested Corrections of the Problem: (e.g. change calibration factor and recompute, flag data with this comment, etc.) Flag data with this comment. 7.7 E20 Soil Probes #3 Cables Cut Platform/Measurement: EBBR/Soil Temperature What location was the data collected at: E20, Meeker, OK Period of time in question: Begin Date 06/11/97 End Date 07/16/97 Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: The cables going to #3 soil temperature, moisture, and heat flow probes were cut by a mower on 11 June 1997 and were repaired on 16 July 1997. Data for the temperature probe was offscale, for the soil moisture probe was a constant 10.1 (close to the actual), and for the soil heat flow was large negative during the period. The following are the data quantities that were affected: 30 minute: ts3, ces3, shf3, c_shf3, cs3, g3, ave_shf, e, h Sensible, latent, and soil heat fluxes can be recalculated using the values from probes 1, 2, 4, and 5, as follows. ave_shf = (g1 + g2 + g4 + g5)/4 e = -(q + ave_shf)/(1 +bowen) h = -(e + ave_shf +q) 7.8 E22 EBBR Right AEM Probes Stolen Platform/Measurement: What location was the data collected at: E22, Cordell, OK Period of time in question Begin Date 6/13/97 Time 0305 GMT End Date 7/16/97 Time 1500 GMT Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: On 13 June 1997, vandals stole the right AEM aspirator unit, including the thermocouple and T/RH probe inside. These were replaced on 16 July 1997. Incorrect data fields during the period above are: 30 minute: tair_top, tair_bot, thum_top, thum_bot, hum_top, hum_bot, vp_top, vp_bot, bowen, e, h 7.9 Wind Direction Malfunction Platform/Measurement: EBBR, wind direction What location was the data collected at: E12, Pawhuska, OK Period of time in question Begin Date 06/03/97 Time 1200 GMT End Date 06/08/97 Time 1515 GMT Data should be labeled: _x_ incorrect _x_ Only some data fields affected Discussion of Problem: For much of the period above, a malfunction in the E12 EBBR wind direction sensor (insect larvae shorting out the circuit board) caused incorrect values for 5 minute res_ws, wind_d, and sigma_wd, 15 minute mv_wind_d, and 30 minute res_ws, wind_d, and sigma_wd. Wind direction normally indicated north (near 0 or 360 degrees); there were some times during the period when wind directions looked good, but the lack of variation in direction and sigma implies that the data is suspect. Therefore, it would be wise to flag all of the values listed above during the entire time period as incorrect. The wind direction sensor (S/N 3081) was replaced with S/N 3042 at 1515 GMT on June 8, 1997. Other observations/measurements impacted by this problem: Resultant wind speed is incorrect: under this condition it has the same value as mean wind speed. Sigma of wind direction is incorrect. 7.10 E13 EBBR CR10 Malfunction Platform/Measurement: What location was the data collected at: E13, Central Facility Period of time in question Begin Date 7/17/97 Time 0930 GMT End Date 7/25/97 Time 1600 GMT Data should be labeled: _X_ incorrect _X_ Only some data fields affected Discussion of Problem: The CR10 apparently malfunctioned on 17 July 1997. This caused a variety of effects, including incorrect datalogger clock times, missing data periods, and some corrupted data fields. The CR10 was replaced on 25 July 1997; all data fields are now correct. Data users may contact the mentor for more detailed information on data quality during this period. 7.11 E8 EBBR Program Compile Error, Effect On Net Radiation Platform/Measurement: EBBR/Net Radiation What location was the data collected at: E8, Coldwater, KS Period of time in question Begin Date 6/10/97 Time 2030 GMT End Date 7/14/97 Time 0915 GMT Discussion of Problem: An error in CR10X program compilation occurred when new software was used to perform the compilation. The new software created an erroneous data table listing, which the program works off of. An incorrect data location was used in the adjustment of net radiation for wind speed, causing all net radiation values to be divided by 2. The following data was incorrect during the period above: 30 minute: q, e, h The latent and sensible heat fluxes can be corrected by recomputing as follows: e = -(2q + ave_shf)/(1 + bowen) h = -(e + ave_shf + 2q) 7.12 E8 EBBR Lightning Strike Platform/Measurement: EBBR/Numerous What location was the data collected at: E8, Coldwater, KS Period of time in question Begin Date 07/14/97 Time 0915 GMT End Date 08/05/97 Time 2300 GMT Discussion of Problem: A lightning "strike" to the EF 8 Facility shortly after 0900 GMT on 14 July 1997 caused the failure of several EBBR sensors, the solar panel voltage regulator, and the CR10X datalogger. All data is missing for the period above, with degraded operations thereafter for a couple of months while replacement parts slowly became available (a separate DQR will cover the degraded data period). 7.13 E19 Soil Heat Flow Probe #5 Upsidedown Platform/Measurement: EBBR/Soil Heat Flow What location was the data collected at: E19, El Reno, OK Period of time in question Portions of: Begin Date 05/29/97 at installation End Date 08/14/97 Time 1500 GMT Discussion of Problem: Soil heat flow probe #5 was installed upsidedown at the initial installation of the EBBR system. The data from it had the wrong sign. Site operations personnel reversed it's orientation in the soil on August 14, 1997, thereby correcting the problem. Values affected (and thus incorrect) include: 30 minute: shf5, c_shf5, g5, ave_shf, e, h. The latent and sensible heat fluxes can be recalculated by reversing the sign of cshf5, adding it to ces5 and recomputing the average soil heat flow, ave_shf = (g1 + g2 + g3 + g4 + g5)/5 e = -(q + ave_shf)/(1 + bowen) h = -(e + ave_shf + q). 7.14 E13 EBBR Missing Data Platform/Measurement: What location was the data collected at: E13, Central Facility, OK Period of time in question Date 7/22/97 Time 0000 GMT Date 7/23/97 Time 0000 GMT Date 7/24/97 Time 0000 GMT Discussion of Problem: The EBBR EF13 data during the periods above is missing. This may be related to a CR10X clock problem that was observed at the time by the SDS. 7.15 E4 EBBR Missing Data Platform/Measurement: What location was the data collected at: E4, Plevna, KS Period of time in question Begin Date/Time 7/09/97 1930 GMT End Date/Time 7/24/97 1530 GMT Begin Date/Time 7/25/97 1130 GMT End Date/Time 8/06/97 0200 GMT Discussion of Problem: Data was not collected remotely for the periods above. The reason for this is unknown. 7.16 E22 Soil Heat Flow Probe #5 Incorrect Data Platform/Measurement: EBBR/Soil Heat Flow What location was the data collected at: E22, Cordell, OK Period of time in question Portions of: Date 07/30/97 Time 1700-1830 GMT Discussion of Problem: Soil heat flow probe #5 produced large negative (and incorrect) values during the period above. The probe was replaced. Somehow, two half hour records were produced at 1900 GMT as a result, the first record having 9s for the data fields; the second record is correct. Values affected (and thus incorrect) include: 30 minute: shf5, c_shf5, g5, ave_shf, e, h. The latent and sensible heat fluxes can be recalculated by using only soil heat flows 1, 2, 3, and 4 to calculate the average soil heat flow, ave_shf = (g1 + g2 + g3 + g4)/4 e = -(q + ave_shf)/(1 + bowen) h = -(e + ave_shf + q) 7.17 E2 Half Hour Incorrect Platform/Measurement: EBBR/all measurements What location was the data collected at: E2, Hillsboro, KS Periods of time: Date 07/08/97 Time 1500 GMT Discussion of Problem: During one half hour period all data is incorrect. The problem appears to be just a bad record as the two 15 minute periods during the half hour were not affected. The cause of the problem is unknown. 7.18 E8 EBBR SHF2 Incorrect Platform/Measurement: EBBR/Soil Heat Flow What location was the data collected at: E8, Coldwater, KS Period of time in question Begin Date 07/14/97 Time 0900 GMT End Date 10/29/97 Time 2000 GMT Discussion of Problem: Soil heat flow probe #2 outputted incorrect, large positive values during the period above. Replacement of the probe on 29 October 1997 corrected the problem. The serial number of the probe replaced is 923025 and of the replacement probe is 923110. The data affected (and thus incorrect) includes: 30 minute: shf2, c_shf2, g2, ave_shf, e, h. The latent and sensible heat fluxes can be recalculated by using only soil heat flows 1, and 3 through 5 to calculate the average soil heat flow, ave_shf = (g1 + g3 + g4 + g5)/4 e = -(q + ave_shf)/(1 + bowen) h = -(e + ave_shf + q) 7.19 E19 EBBR Battery Voltage Drop Period of time in question Begin Date 05/29/97 End Date 12/31/97 Time 1520 GMT Discussion of Problem: EBBR battery voltage at E19, El Reno, OK declined to lower than acceptable levels after long periods of clouds after initial installation. The low voltage condition worsened as Autumn progressed. In November 1997 the battery tested okay, but would not hold sufficient capacity at night or during extended periods of clouds to keep the voltage high enough for the EBBR to work properly. At my request, the battery was replaced with a brand new battery on 31 December 1997. The new battery is presently maintaining voltage level at night. The voltage dropped to 10 volts or less many days before the battery change. Voltages less than 10.3 volts affected a wide range of measured values, but at different times. When the voltage was much below 10 volts the home signal became very large (several volts), a quirk of the AEM circuitry. At various times, latent and sensible heat fluxes, soil temperature, air temperature, relative humidity, vapor pressure, wind direction, soil heat flux plate output, home signal, and atmospheric pressure (at least) were not reported correctly by the CR10 datalogger. At least the sensible and latent heat fluxes should be considered to be incorrect when the battery voltage is less than 10.3 volts. The battery voltage is found in the 15 minute data. 7.20 Character In EBBR E26, 30 Minute Data START DATE: 06/18/1997 START TIME: 200 END DATE: 06/18/1997 END TIME: 200 A non-numeric character appears in the field for shf1 in the 30 minute data file at the time shown above. Data processing programs that assume that a numeric character is there will display an error condition. I had to create a short routine to put in my analysis program to avoid using that data point. 8.0 Assessment of Instrument Calibration and Maintenance Procedures from work for site scientist Preventative Maintenance Procedure Summaries for the EBBR at the Southern Great Plains (SGP) Site A1) What are factory recommended calibration procedures? FC1: Humidity: Three-point calibrations (at approximately 11%, 75%, and 97%) above saturated salt solutions are used. [Factory calibration at 0% and 75% referenced to NIST] FC2: Temperature Sensors: There are ten temperature sensors in the EBBR system: two platinum resistance temperature detectors (PRTD) in the exchanging aspirated radiation shields, two thermocouples in the exchanging aspirated radiation shields, one reference PRTD in the control box, and five PRTD soil probes. All temperature sensors are subjected to an eight-point calibration (-30 to 40 deg C) in a XLT Heat Transfer Fluid (a silicon fluid) bath. A laboratory standard NIST-traceable PRTD is used for the reference. The laboratory standard PRTD data are acquired with a Campbell Scientific CR10 Datalogger, using the CR10 resistance-to-temperature function. Sensor PRTD normalized resistance ratio is measured with a CR10 datalogger and regressed versus laboratory standard temperatures to obtain polynomial coefficients for the EBBR CR10 software. Thermocouple output is measured with a CR10 analog channel and the Campbell Thermocouple Function; the CR10 panel reference platinum element is used as the reference temperature sensor, located at the point where the thermocouples connect to the multiplexer. Deviations between the Laboratory Standard and thermocouple temperatures are recorded. FC3: Soil Moisture Probe: Soil moisture probes are calibrated in a ceramic pressure plate extractor, in Kennewick, WA, soil. (Note: 1995 calibrations for Meeker, OK, E20 and for Elk Falls, KS, E7 were initially performed in soil from the respective site. These sensors were replaced in early 1996 with sensors calibrated in Kennewick, WA, soil). The extractor pressure gauge is traceable to NIST. Soil moisture probe and pressure gauge data are acquired with a CR10. Until April 1996, regression analyses were used to determine polynomial coefficients for the relationship between the normalized resistance ratio and the natural logarithm of pressure. A second polynomial converted pressure into soil moisture percent by weight using empirically determined polynomial coefficients for clay loam soil. The polynomial coefficients were used in the EBBR CR10 software. In April 1996, the method of calibrating soil moisture probes from the probe and pressure plate data was modified. Soil moisture is now calculated directly from probe resistance, normalized to 25 degrees C. This produces a nearly linear relationship that requires the use of only one polynomial in the CR10 software and results in a significantly extended range of measurement of soil moisture. FC4: Soil Heat Flux Transducer: The soil heat flow transducers are calibrated in a water-saturated glass bead medium that is located between hot and cold temperature baths. Heat transfer across the medium is determined from the temperature gradient between the baths. Bath temperatures are determined with NIST-traceable platinum resistance probes. Corrections are made in the CR10 software for the difference between the calibration medium thermal conductivity and the transducer thermal conductivity. FC5: Net Radiometer: Calibration is performed in a temperature-controlled chamber against a net radiometer transfer standard. The light source is a tungsten-halide lamp. The transfer standard is calibrated against an Eppley precision pyranometer. The transfer standard is traceable to NIST through the Eppley pyranometer using a shading technique. Note: some difference in calibration for short and long wavelengths has been noted by REBS and ARM, and is partially the result of calibrations versus a standard that is itself calibrated only against a pyranometer (which measures primarily short wavelengths), and partially a result of net radiometer design. FC6: Barometric Pressure: The barometric pressure sensor is calibrated by the manufacturer at three pressure levels (27, 29 and 31 or 25, 27, and 29 depending on the model) inches of mercury. Two models manufactured by the same company are presently in use. Electronic adjustments are made to bring the sensor within specifications. FC7: Wind Direction Sensor: Calibration consists of alignment of the potentiometer and drive coupler to produce a voltage output corresponding to 180 deg when the sensor hub and column marks are lined up. The manufacturer uses a precision degree wheel, pointer assembly, and digital voltmeter for the procedure. FC8: Wind Speed Sensor: Calibration consists of spin tests by the manufacturer at various rotation rates to ensure that the sensor meets frequency versus speed specifications. Wind Tunnel calibrations are not performed. FC9: CR10 Datalogger: All connections to the CR10 are removed and reference voltages or frequencies inputted to determine if outputs are as specified by the manufacturer. A2) What are the factory recommended performance checks? Despite the vendors usage of the word "calibration" below, the following are checks, not calibrations. FP1: 6-Month - Air Temperature Thermocouples Field Calibration Check FP2: 6-Month - Aspirated Radiation Shields Flow Rate Check vs. Airvane FP3: 6-Month - Barometer Field Calibration Check FP4: 6-Month - Vaisala Humidity Probes Field Calibration Check FP5: 6-Month - Vaisala Temperature Probes Field Calibration Check A3) What are the mentor calibration procedures? Return to vendor annually for recalibrations (see A7). Note: the vendor recommends recalibration of the soil moisture and temperature probes every 6 months. A4) What are the mentor performance checks? MP1: 3-Month Checks - Wind Speed Sensor MP2: 3-Month Checks - Wind Direction Sensor MP3: 3-Month Checks - Barometric Pressure MP4: 3-Month Checks - Air Thermocouple and PRTD Temperature Probes MP5: 3-Month Checks - Relative Humidity Probes MP6: 3-Month Checks - Aspirator Fans Flow Rate with Airvane MP7: Bi-weekly Checks - Wind Speed Sensor MP8: Bi-weekly Checks - Wind Direction Sensor MP9: Bi-weekly Checks - Temperature Sensors MP10: Bi-weekly Checks - Barometeric Sensors MP11: Bi-weekly Checks - Humidity Sensors A5) How are calibration and related performance checks documented? 1. Where are procedures documented? All calibration and performance check procedures are documented at site operations. 2. Have major changes to calibration procedures occurred? If so, for which components and when? No major changes to field "calibrations" and checks have occurred. Vendor calibration procedures for soil moisture sensors changed significantly in September 1995. 3. Are major changes to calibration procedures expected to occur? If so, for which components and when? No. A6) Who implements (mentor) calibration and performance checks? Mentor: none Factory: FC1-9 Site Ops: MP1-11 Other _________: A7) What is standard schedule of calibrations and checks? Each EBBR system is scheduled for return to the EBBR provider annually for recalibration/replacement of all probes, sensors, and data acquisition equipment. Because of the turn-around time for each system recalibration, the schedule may slip to every 1.5 to 2 years if needed. The 3-month sets of checks have been implemented for the EBBR stations in operation. Bi-weekly checks occur regularly for each system. Scheduled Calendar Event: MP1-11 Work Order (from mentor request): FC1-9 Data Inspection: (see "Work Order") Instrument Failure (from mentor request, site ops action): FC1-9 Other__highest priority basis__: FC1-9 A9) How long does it take to perform calibration and performance check procedures? The times below assume that no problems are discovered; if R/R is needed, the length of time is greater. MP1-5: 60 to 90 minutes MP6-11: 20 to 30 minutes FC1-9: 1 month A10) Are any data affected or lost during calibration or performance check procedures? Data loss is not likely during bi-weekly checks as the system is not powered down during servicing. Data will be affected during the 3-month checks since the AEM is disabled during some of the checks. A11) What are corrective procedures when calibrations and or performance checks fall behind schedule? Revise schedule or divert resources to bring up to schedule. B. Calibration Data B1) Where are calibration data documented? Site Data System: none Site Ops Data base - Hard Copy: i)EBBR Manual, ii) Instrument Inventory /Calibration Sheet, iii) 3-month Check Sheets Site Ops Data base - Electronic Copy: Site Ops Log contains some information on times and activities. Instrument Mentor - Hard Copy: same as for Site Ops Data base Instrument Mentor - Electronic Copy: Site Ops Log Data Logger: Data during checks. netCDF file: Data during checks. Special Archive Database: none Special Databases Accessbile via the WWW: none B2) Where are calibration coefficients and algorithms applied to convert data to geophysical units? Data Logger C) Maintenance Procedures: C1) What are the factory recommended maintenance procedures: (preventive and corrective)? FPM1: Annual - Wind Direction Bearing Replacement FPM2: 6 monthly - Wind Speed Sensor Bearing Replacement FPM3: 3 monthly - Wash AEM belt/channel FPM4: 3 monthly - Replace Radiometer Domes FPM5: Weekly - Air Temperature Thermocouples: Inspect/Clean FPM6: Weekly - AEM: Inspect Cycling FPM7: Weekly - Barometer: Inspect/Clean Inlet Port FPM8: Weekly - Data Logger: Inspect if data abnormal FPM9: Weekly - Battery: Inspect/Add Water/Replace if needed FPM10: Weekly - Frame: Inspect/Tighten FPM11: Weekly - Heat Flow Transducers: Inspect Cabling FPM12: Weekly - J-Panels: Inspect if data abnormal FPM13: Weekly - Modem: Inspect if problems occur FPM14: Weekly - Multiplexer: Inspect if data abnormal FPM15: Weekly - Net Radiometer: Inspect/Level/Clean/Replace dome(s) FPM16: Weekly - Reference Temperature: Inspect if data abnormal FPM17: Weekly - Soil Moisture Probes: Inspect Cabling FPM18: Weekly - Soil Temperature Probes: Inspect Cabling FPM19: Weekly - Solar Panel: Inspect FPM20: Weekly - Storage Module: Inspect if problems occur FPM21: Weekly - Vaisala Humidity Probes: Inspect/Replace filter if dirty FPM22: Weekly - Vaisala Temperature Probes: Inspect FPM23: Weekly - Wind Direction Sensor: Inspect/Adjust Heaters FPM24: Weekly - Wind Speed Sensor: Inspect/Adjust Heaters Note: Replacement of the SM716 battery is recommended by the manufacturer every 6 years. However, this activity may be accomplished during the annual recalibration. FCM1: FCM2: C2) What are the mentor preventative and corrective maintenance procedures? PM1: 6 monthly - Wind Speed Sensor Bearing Replacement PM2: 3 monthly - AEM: Inspect/Clean/Repair & Replace needed parts PM3: 3 monthly - Radiometer Domes: Replace PM4: 3 monthly - Wind Speed Sensors: Service, Repair & Replace if needed PM5: 3 monthly - Wind Directions Sensors: Repair & Replace if needed PM6: 3 monthly - Barometric Pressure: Inspect PM7: 3 monthly - Control Box: Inspect/Repair if needed PM8: 3 monthly - Cables: Inspect, Repair & Replace PM9: 3 monthly - Fans: Check Flow, Repair and Replace PM10: 3 monthly - Soil Probes: Inspect, Repair and Replace PM11: Bi-Weekly - Air Temperature Thermocouples: Inspect/Clean PM12: Bi-Weekly - AEM: Inspect Cycling/Move up if vegetation is too tall PM13: Bi-Weekly - Barometer: Inspect/Clean PM14: Bi-Weekly - Data Logger: Inspect if data abnormal PM15: Bi-Weekly - Battery: Inspect/Add Water PM16: Bi-Weekly - Frame: Inspect/Tighten PM17: Bi-Weekly - Heat Flow Transducers: Inspect Cabling PM18: Bi-Weekly - J-Panels: Inspect if data abnormal PM19: Bi-Weekly - Modem: Inspect if problems occur PM20: Bi-Weekly - Multiplexer: Inspect if data abnormal PM21: Bi-Weekly - Net Radiometer: Inspect/Level/clean PM22: Bi-Weekly - Reference Temperature: Inspect if data abnormal PM23: Bi-Weekly - Soil Moisture Probes: Inspect Cabling PM24: Bi-Weekly - Soil Temperature Probes: Inspect Cabling PM25: Bi-Weekly - Solar Panel: Inspect PM26: Bi-Weekly - Storage Module: Inspect if problems occur PM27: Bi-Weekly - Vaisala Humidity Probes: Inspect/Replace filter if dirty PM28: Bi-Weekly - Vaisala Temperature Probes: Inspect PM29: Bi-Weekly - Wind Direction Sensor: Inspect/Adjust Heaters PM30: Bi-Weekly - Wind Speed Sensor: Inspect/Adjust Heaters PM31: Bi-weekly - Adjust grass height inside fence to the height outside. PM32: Bi-weekly - Reduce vegetation height under electric fence. CM1: CM2: C3) How are maintenance procedures documented? 1. Where are procedures documented? Site Ops hard copy. 2. Have major changes to maintenance procedures occurred? No. If so, for which components and when? 3. Are major changes to maintenance procedures expected to occur? No. If so, for which components and when? C4) What is the procedure schedule? (see C1 and C2) C5) How are the procedures initiated (queued)? Scheduled Calendar Event: PM11-32, PM2-10, PM-1 (not yet scheduled) Work Order: Any maintenance activity may be triggered by request from the mentor or site ops. Data Inspection: May result in a request for maintenance or checks from mentor or site ops. Instrument Failure: May result in a request for maintenance by mentor or site ops. Other_______: C6) How long does it take to perform maintenance procedure? The times below assume that no problems are discovered; if R/R is needed, the length of time is greater. PM1: 15 minutes PM2-10: 30 minutes PM11-32: 30 minutes C7) Are any data affected or lost during maintenance procedure? Data not affected during PM11-32 unless R/R performed. Data affected during PM1-10; AEM is disabled. Data lost during PM-1; R/R of bearings/sensor. C8) How are potential affects to data documented? Site Operator Instrument/Data Trouble Report/Site Ops. Log DQRs submitted by mentor. C9) What are corrective procedures when maintenance falls behind schedule? Revise schedule/divert resources to bring up to schedule. C10) Where is actual maintenance work documented? Site Ops - Hard Copy Site Ops Log (eletctronic) DQRs by mentor. D) Data Integrity and Quality Inspections D1) What nodes or activities along the data pipeline affect (or can potentially affect) the data stream? Controller Boxes Data Logger Communication lines/links D2) What are current difficulties? AEM malfunctions; a design change appears to have reduced this. Dome condensation. Frozen wind sensors during winter, particularly for sites without AC power. Low battery voltage, particularly in winter at sites without AC power. Low aspiration; not usually a problem when site ops checks the fans diligently every 2 weeks. Wind Direction malfunctions; this can result in incorrect soil moisture #2 data because of a multiplexer quirk. D3) List and describe any standard or non-standard data inspections (active or planned) under each of the following categories: Data Existence check: Site Ops: Check for raw .a0 and .a1 files Mentor: tracks missing half hours and submits a list of sneakernet data days to be ingested to fill in the missing data. Mentor QC checks (during ingest): Mentor Min/Max Checks on some 15- and 30-minute data; no Delta checks Mentor QC checks (outside of ingest) Mentor inspection of the data on a regular basis, comparison of data from adjacent systems and sites. D4) Do storage media exist on the instrument system to back up data and store it for delayed data ingest? Please identify media and the maximum period of time that the data can be backed up on the media. SM716 Storage Module - 15.7 days CR10 Datalogger Memory - 1 day, 7 hours 9.0 Calibration Theory Standard calibration procedures are used. A description of the procedures is given in item A1 of the section Assessment of Instrument Calibration and Maintenance Procedures. 10.0 Calibration History The first set of dates for SEBS units 1 through 10 below are the initial field installation dates. Subsequent dates for SEBS units 1 through 15 are the dates of installation of recalibrated systems (note: these dates can be much later than the removal date for the previous location of the system because of the significant length of time required for recalibration of a system). The extended facility site at which the unit was installed after calibration or recalibration is also listed. NOTE: SEBS Unit numbers do not normally correspond to Extended Facility site numbers! Unit 1 - E13 - 14 September 1992 - E12 - 9 October 1996 Unit 2 - E28 - 10 June 1992 - E26 - 21 July 1993 (note: system remained in same location, site number was modified) - E2 - 23 May 1997 Unit 3 - E15 - 16 September 1992 - E22 - 7 November 1996 Unit 4 - E9 - 10 December 1992 - E8 - 30 July 1996 Unit 5 - E8 - 8 December 1992 - E19 - 29 May 1997 Unit 6 - E20 - 5 April 1993 - E9 - 15 November 1995 Unit 7 - E22 - 5 April 1993 - E18 - 10 September 1997 Unit 8 - E4 - 3 April 1993 - E26 - 17 July 1996 Unit 9 - E7 - 29 August 1993 - E13 - 24 May 1996 Unit 10 - E12 - 29 August 1993 - E25 - Unit 11 - E20 - 9 August 1995 Unit 12 - E4 - 25 October 1995 (placed at wrong location initially) - E7 - 2 November 1995 (proper location) Unit 13 - E4 - 1 November 1995 Unit 14 - E15 - 14 December 1995 Unit 15 - E20 - 11.0 Current Status and Locations Fourteen EBBR systems are presently installed and operating at extended facilities. EBBR systems are located at: E2 Hillsboro, KS E4 Plevna, KS E7 Elk Falls, KS E8 Coldwater, KS E9 Ashton, KS E12 Pawhuska, OK E13 Central Facility, Lamont, OK E15 Ringwood, OK E18 Morris, OK E19 El Reno, OK E20 Meeker, OK E22 Cordell, OK E25 Seminole, OK E26 Cement, OK 12.0 Calculated Data 12.1 Value Added Procedures Recalculation of sensible and latent heat fluxes using SIRS net radiation information (not presently implemented). This approach may help to improve flux estimates during times when the EBBR net radiation data is corrupted by dew, frost, or condensation inside or outside of the net radiometer domes. Recalculation of sensible and latent heat fluxes using wind speed and temperature gradient information in conjunction with a bulk aerodynamic estimation technique (not presently implemented). These calculations would help to produce more reasonable estimates of fluxes when the Bowen ratio is near -1 (the Bowen ratio technique often produces unreasonable flux values under this condition). 12.2 Quality Measurements Experiments Comparison of EBBR measured net radiation and SIRS calculated net radiation (not presently implemented). Comparison of sensible and latent heat fluxes from EBBR and ECOR systems (not currently implemented and only for comparisons using the portable Eddy Correlation System; no permanent Eddy Correlation Systems will be colocated with EBBRs over the same vegetation surface). 13.0 Examples of Data Quick Looks: Daily Plots and Weekly Plots, from the ARM Science Applications Group Daily Plots, from the SGP Site Data System Seen below is a graph of EBBR data on a day with an annular solar eclipse at about 1700 GMT (same as UTC in graph). The graph shows sensible heat flux (H), latent heat flux (LE), and net radiation minus soil surface heat flux (Rn-G). The estimates were made with the EBBR technique and a bulk aerodynamic (BA) method at the SGP CART central facility on a cloudless day. A "spike" occurred in the EBBR H and LE estimates at 115 GMT because the Bowen ratio had a value near -1. The BA method can be used to remove such spikes, which usually occur 1 to 5 times per day, particularly near sunrise and sunset. Further details about the graph can be found in Wesely et al. 1995 (see Citable References). 14.0 Instrument Mentor notes on data quality control procedures QC frequency: once per week QC delay: QC type: graphical plots, printouts of 15- and 30-min. data, comparisons of data Inputs: raw data plots Outputs:DQRs; summary reports to site scientist team Reference: Data quality control procedures for this system are mature. Instrument mentor David Cook inspects EBBR data from all sites at least once per week. He reports data deficiencies via DQRs, and periodically sends summary reports to the SGP site scientist team. David uses several means to inspect the data. He inspects plots at the LLNL Web site to look for obvious problems and to identify the approximate times of problems; inspects printouts of tables of 15-min and 30-min data to investigate problems more thoroughly; and compares data from various extended facilities to help identify and interpret the problems. He uses computer programs to compare some of the EBBR data to those from surface meteorological observation stations (SMOSs). David also examines weekly MDS summaries to determine when and how preventative and corrective maintenance responds to his work requests. 15.0 Explanation of Flags Applied During Data Ingest QC flags are used for the 15 and 30 minute data ingests. No QC flags are used for the 5 minute data ingest. Explanation of these flags is given below. 15 minute data: Variable: rr_sm#, # = 1, 2, 3, 4, 5; min = -0.2, max = 1.25 (before late April 1996) Explanation: Soil moisture Resistance Ratio is small for high soil moisture and large for low soil moisture. The polynomials used in calculating soil moisture exhibit wild and non-real behavior for low or high resistance ratios. Therefore, a min and max are set to indicate when such conditions occur. Variable: r_sm#, # = 1, 2, 3, 4, 5; min = 0.0, max = 100.0 (after late April 1996) Explanation: Soil moisture probe resistance (kohms) is small for high soil moisture and large for low soil moisture. The calibration of the probe is nearly linear, so values outside these limits indicate non-real values. The vendor changed to using resistance (instead of resistance ratio) to calibrate the soil moisture probes to allow a greater range of soil moisture to be measured with increased accuracy. However, because it required several months to change all of the CR10 programs to the new resistance measurement, the ingest erroneously reported some incorrect soil moisture qc values. By mid-November 1996, all EBBR systems had been changed over to resistance for the 15 minute values. During the intervening period, the 30 minute soil moisture qc values should be relied upon more heavily for determination of soil moisture quality. Variable: bat; min = 10 volts, max = 17 volts Explanation: EBBR battery voltage can vary considerably because the battery is kept charged with a solar panel. A regulator on the solar panel is designed to prevent charging of the battery to greater than 14.5 volts DC. If a voltage of greater than 17 volts occurs, a number of components of the EBBR are vulnerable to damage. Therefore, the max QC flag would probably indicate failure of the voltage regulator and also serves as a warning to site operations and/or the mentor that immediate action is required to prevent damage to components. Data is not normally affected at voltages up to 17 volts, but can be at voltages near 18 volts. The min QC flag could indicate that one of the following conditions exists: poor battery condition (will not recharge properly), voltage regulator malfunction, solar panel malfunction, poor connection of DC voltage cables to the battery, AEM malfunction that has not blown a fuse is draining the battery, or insufficient sunlight over an extended period to keep the battery charged (a common problem in conjunction with batteries in poor condition in the winter). Some EBBR components will not function properly or at all during low battery voltage conditions. The CR10 datalogger will normally log data even at 10 volts, but the quality of the data is suspect. 30 minute data: Variables: tref, tair_top, tair_bot, thum_top, thum_bot, ts#, # = 1, 2, 3, 4, 5; min = -50 degrees C, max = 50 degrees C Explanation: All air and soil temperatures have the same max and min. Values outside this range should be considered to be incorrect, although unusual temperature extremes are possible. Variables: hum_top, hum_bot; min 0, max 1.02 (fraction; multiply by 100 for %) Explanation: The minimum is self-explanatory. The capacitive relative humidity element is subject to an offset drift of up to 0.04 per year; this results from aging of the element materials and from contamination by soil, etc. The max QC flag alerts the user to the possibility that an offset drift has occurred. Both RH probes may have experienced the same drift; this is most easily checked by looking at the output of each during saturated (100% RH) conditions. Variable: q (net radiation); min = -1500 watts per meter squared, max = 1500 watts per meter squared Explanation: Typical net radiation values for the SGP CART Site are -100 to 1100 watts per meter squared. The min QC is clearly much smaller than it needs to be. Exceedence of either the max or min should indicate a malfunctioning net radiometer. Variable: pres (atmospheric barometric pressure, not corrected to mean sea level); min = 80 kPa, max = 120 kPa Explanation: Atmospheric barometric pressure values at the SGP CART Site are typically in the range of 93 to 105 kPa; therefore, values outside the max and min values should be considered as incorrect. Variables: sm#, # = 1, 2, 3, 4, 5; min = 1%, max = 50% Explanation: Most of the soil moisture probes indicate saturated soil when they approach 40%; data values greater than 50% are probably unrealistic. The probes are not accurate below about 3% or above 45%. Variables: shf#, # = 1, 2, 3, 4, 5; min -500 watts per meter squared, max 500 watts per meter squared Explanation: Soil heat flow (measured with the soil heat flow probes) at the SGP CART Site is normally within the range of -100 to 100 watts per meter squared. Values outside the max and min indicate a malfunction of a probe. Variable: wind_s (wind speed); min = 0 m/s, max = 100 m/s Explanation: Wind speeds rarely exceed 30 m/s for a 30 minute period at the SGP CART Site. Variable: wind_d (wind direction); min = 0 degrees, max = 360 degrees Explanation: Wind direction, by definition is restricted to the max, min range. Values outside this range are incorrect. Variable: home_15 (AEM position indicator); min = 35 mv, max = 70 mv (see section 4. of Frequently Asked Questions (FAQs) for an explanation of the meaning of the home signal values) Explanation: This is the AEM position indicator for the first 15 minutes of the 30 minute data period. The mv value is proportional to battery voltage and therefore can vary considerably in the max, min range. If it is less than 35, the battery voltage may be too low to produce correct data. Furthermore, the EBBR datalogger programming will think that the AEM is actually in the 15 to 30 minute position and will incorrectly calculate sensible and latent heat fluxes. The home_15 value can be larger than 70 and still indicate the proper AEM position, but this situation indicates that there is a problem with the AEM home signal voltage circuitry (a transistor short or a resistor failure can cause the home_15 and home_30 outputs to be electronically added). A home_15 value near zero indicates that the AEM has halted at a position between the top and bottom, resulting in incorrect sensible and latent heat flux values. Other conditions are also possible, although uncommon; see the mentor for more details, if needed. Variable: home_30 (AEM position indicator): min = 15 mv, max = 34.999999 mv (see section 4. of Frequently Asked Questions (FAQs) for an explanation of the meaning of the home signal values) Explanation: This is the AEM position indicator for the last 15 minutes of the 30 minute data period. For battery low voltage conditions the home_30 value can be less than the min value and not mean that the 30 minute flux data is incorrect or that the AEM is not in the proper position.. However, the low battery condition itself may result in incorrect data. If the home_30 value is near zero, it probably indicates that the AEM has halted at a position between the top and bottom, resulting in incorrect sensible and latent heat flux values. Other conditions are also possible, although uncommon; see the mentor for more details, if needed. 16.0 Frequently Asked Questions FAQs 1. How are the latent heat flux and sensible heat flux derived? See the section Theory of Operations. 2. What is the sign convention used for the energy flux densities? All energy flux densities have a positive sign when directed toward the surface and negative when directed away. For example, some values of latent heat flux (LE) could be -100 to -500 watts per meter squared during the daytime in the summer. 3. In the design of the EBBR stations, which data are considered the most useful to ARM Science Team members? The EBBR stations were designed primarily for computation of the sensible and latent heat fluxes. The soil temperature, moisture, and heat fluxes are only rough estimates that should be used with considerable caution. Other observations, such as air temperature, relative humidity, atmospheric pressure, and wind speed and direction are secondary. For example, the EBBR atmospheric pressure data is not measured with sufficient accuracy for many applications, whereas the SMOS pressure data has a smaller uncertainty and might be suitable for calculations of geostrophic winds. Other sources of reliable surface meteorological data are available as external data in the ARM program from the Oklahoma Mesonet and from the Kansas network. The data user is encouraged to use the data from the surface meteorological observation station (SMOS) for such observations. EBBR data are collected only at CART extended facilities, including one at the central facility and some collocated with boundary facilities, and where the local surface is not tilled. Eddy correlation stations exist or will exist at nearly half of the extended facilities to sample the latent heat, sensible heat,and momentum fluxes above tilled fields. EBBR data can be used to compute momentum fluxes with a bulk aerodynamic approach. A computer program written in Fortran for this purpose is available from Marv Wesely and may eventually be implemented at the ARM experiment center as an alternative data stream. One significant advantage to having this data stream is that unwanted spikes can be detected when the Bowen ratio is near -1. This approach is briefly summarized in an extended abstract titled "Surface Heat Flux Data from Energy Balance Bowen Ratio Systems" by R. L. Coulter, D. R. Cook, and M. L. Wesely (Preprints, Ninth Symposium on Meteorological Observations and Instrumentation, Charlotte, NC, 27-31 March 1995, American Meteorological Society, Boston, MA, pp. 486-489. 4. What do the AEM (Automatic Exchange Mechanism) home signals indicate? The AEM home signal outputs in the 5, 15 and 30 minute data streams are in units of millivolts DC. The circuitry producing the millivolt output is fairly rudimentary and therefore the millivolt value is proportional to the DC voltage output of the power supply (solar/AC charged battery) that provides power for the EBBR. The home signal can therefore vary significantly diurnally and can fall to unacceptable levels for the 15 minute value if batery performance degrades too much. The right side (looking from behind the AEM) aspirated radiation shield (housing temperature and relative humidity probes) is normally in the "bottom" (lowest elevation) position and the left side in the "top" (greatest elevation) position during the first and third quarter hours; the 5 minute "home", 15 minute "mv_home", and 30 minute "home_15" values should be between 40 and 55 during this AEM state. The left side (looking from behind the AEM) aspirated radiation shield (housing temperature and relative humidity probes) is normally in the "bottom" (lowest elevation) position and the right side in the "top" (greatest elevation) position during the second and fourth quarter hours; the 5 minute "home", 15 minute "mv_home", and 30 minute "home_30" values should be between 15 and 30 during this AEM state. See section 7. below for information on abnormal AEM states and incorrect home signal values. 5. What soil measurements are made by the EBBR stations? Five soil heat flux sensors are located at a depth of five centimeters from the surface, five long platinum resistance temperature detectors (PRTD) integrate the temperature from the surface to a depth of five centimeters, and five soil moisture probes are located at a depth of 2.5 cm in individual bags of soil that extend from just below the surface to a depth of five centimeters. Each set of five soil sensors is averaged. Since soil is not horizontally homogeneous, the sensors are spaced out in the soil locally to provide representative samples. The purpose of these sensors is to compute one term, the soil heat flow. The soil temperature and moisture sensors allow calculation of the energy storage in the layer of soil between the surface and a depth of five centimeters, where the flux plates are located. The sensible and latent heat fluxes are computed by the EBBR data logger with the standard energy balance equation, in which the soil heat flux is usually a relatively small term. The soil heat flux term cannot be precisely recalculated from the outputted raw information because of the way that the soil energy storage term is computed with the EBBR data logger but, in principle, the raw information can be used to recompute the sensible and latent heat fluxes with only a few percent error. 6. What type of diurnal trends should appear in the EBBR data? Some examples of diurnal trends can be seen in various textbooks and articles. For example, some data are shown in the special FIFE issue of the Journal of Geophysical Research (Vol. 97, pp. 18,343-19,110), e.g., the article by Fritschen et al. starting on p. 18,697. We are using a Fritschen type EBBR station. 7. What can be said about the quality of the EBBR data? The EBBR systems sometimes experience hardware problems. For example, the automatic exchange mechanism will sometimes malfunction. Some problems, like this one, can be discerned by looking at the data quality flags. See section 4. in this area for an explanation of the meaning of the AEM home signal values. The following information should be useful for interpretation of the quality of data from the EBBR stations. Data quality flags should be used to detect when the automatic exchange mechanism (AEM) is functioning properly. The rate of AEM failure has been high at times. When it is not working, the estimates of sensible and latent heat flux are unreliable and should not be used for any scientific investigations, even if the flux estimates appear to be reasonable. To use the metadata on the AEM, please become familiar with the field and global attributes that are described in a dump of the netcdf header. The fields are defined there, and, in data sets recently provided, the configuration of the data quality flags is briefly described at the end of the list of the global attributes. The flags themselves are contained in numbers at the end of the data listing. The next paragraph provides some suggestions on the quality control numbers (qcmin# and qcmax#) and the imbedded flags relevant to the AEM. Quality control (QC) flags in the standard, 30-min data indicate when the AEM is working for each half hour in the time series. The particular QC flags of interest are the sixth and seventh bits of the 24-bit binary numbers representing qcmin49-72 and qcmax49-72. The sixth bit of qcmin49-72 is set to zero when the home_15 is greater than 35 mV and to unity when less. The sixth bit of qcmax49-72 is set to zero when the home_15 is less than 70 and to unity when greater. A similar set of criteria are applied to the seventh bit but with a minimum of 15 and maximum of 34.999999. Alternatively, if you choose not to convert the quality control numbers to binary form, you can inspect the values of home_15 and home_30 to determine if they fall in the desired range. Because the limit checks on the home signals were not properly set prior to April 7, 1993, you must inspect home_15 and home_30 rather than qcmin# and qcmax# for data collected prior to that date. The QC flags should routinely be used for all of the variables. For some variables, however, QC flags have never been set, and for some variables (e.g., average soil heat flow (ave_shf), latent heat flux (e), and sensible heat flux (h)) flags were not set until late May 1998, as is evident in the listing of the field attributes. Nevertheless, some information can be obtained by inspection of the data if you are familiar with typical values. For example, Bowen ratios tend to be positive during the day and negative at night. Daytime values are usually between 0 and 2, and nighttime values can vary widely between positive values and -50. A negative Bowen ratio during daylight hours should be considered as possibly indicating suspect sensible and/or latent heat flux values. During transition times lasting up to two half hours near sunrise and sunset, the magnitude of the Bowen ratio can sometimes be quite large, in which case the sensible and latent heat flux values should be viewed as suspect. Although no QC flags were set for latent and sensible heat flux, values smaller than -1000 watts per meter squared and larger than 200 watts per meter squared are clearly suspect. Routine checks reveal the expected offset drift of the RH probe of about +2% per year caused by aging and dirt contamination of the RH sensing element. This drift has also been observed in the Tower and SMOS RH probes. Although this affects the absolute accuracy of the RH measurement, it does not adversely affect the 30 minute vapor pressure difference calculated from the RH and temperature measurements because the RH probes drift at approximately the same rate and the exchanging Bowen ratio technique reduces offset affects. Recalibration after 2 years use is usually necessary to keep the RH probes within their "as new" absolute accuracy specification; this is the goal of the EBBR recalibration program conducted every 2 years. The absolute value of the home signals varies with the voltage of the battery that powers the EBBR data acquisition system. When the battery condition is good, the home_15 value is typically between 40 and 55; the home_30 value is typically between 15 and 30. When battery condition is low, the home signals can be slightly lower, but then the data from some individual sensors are questionable. Instances have occurred where low battery condition allowed some sensors to function while others did not. Data Quality Reports (DQRs) are written to identify such problems. Unfortunately, the AEM does not always switch and occasionally hangs up. Four cases are common. A. AEM fuse blown. The positions of the housings on the AEM when the fuse blows (usually a result of too much friction on the exchange mechanism resulting from freezing rain or snow, built up dirt, or an electrical or electronic failure) is uncertain and usually yields home_15 and/or home_30 values of zero, although E15 at Ringwood, OK showed -2.0 in this condition in May 1994. B. AEM stuck at one position. Usually the right housing will stick in the down position (sometimes referred to in site operations log messages as the home position). When this happens, the home_15 and home_30 signal outputs are usually both equal to the proper home_30 value, if the AEM fuse has not blown. There are exceptions to this of course, which included a period at the Central Facility EBBR in late 1992 when both home signals were 35. C. AEM stuck between the 15 and 30 min positions. This situation usually produces a very small negative home value for both home_15 and home_30, such as -0.2. D. AEM removed for service. Occasionally an AEM has been removed from service for repair when no replacements were available. A good example of this situation is when the EBBR at E9, Ashton, KS, was removed on April 5, 1994. A resistor in the AEM circuitry had burned out, leaving the left housing in the bottom position (a rarity). This had resulted in both home signals being somewhere from 67 to 73. After the AEM was removed, the aspirated housings were tied to the EBBR frame, approximately a meter apart. Without the AEM circuitry being present, the home signals floated to the thousands. On April 19 a refurbished AEM was installed and the home signals returned to normal. The list above illustrates only some of the possibilities. It can be generally said that, whatever their absolute values, if the home_15 and home_30 values are practically the same in the 30 min data, at least one of them is incorrect, indicating that the sensible and latent heat flux estimates are suspect. Unless both of the home_15 and home_30 values are within proper ranges, the sensible and latent heat values must be considered incorrect. No other interpretation is appropriate. Even if we know the AEM position situation and could thus recalculate fluxes from the available data, those fluxes would still be corrupted with calibration offsets, which are normally removed via the AEM switching process. Most users of the EBBR data only receive the 30 min data and not the 5 or 15 min data. The QC flags in the 15 min data might be useful for a comprehensive evaluation of each EBBR sensor. For example, the qcmin# check for battery condition in the 15 min data is set to the lowest value at which the sensors will typically operate reliably. Also, soil moisture resistance ratios (rr_sm#, used before April 1996) or soil moisture resistance (r_sm#, used beginning in April 1996) could be examined to help determine when individual soil moisture values are reliable. We do not, however, expect every user of the EBBR to obtain the 15 min data for such analyses. Finally, we caution users of the data that the reliability and accuracy of some individual sensors such as soil moisture sensors may be not optimal. The EBBR system was not designed to observe all quantities extremely well because its primary purpose is to provide sensible and latent heat flux estimates, which are not particularly sensitive to the uncertainties of some of the variables. If you need accurate, reliable estimates of barometric pressure and air temperature, for example, please use the values supplied by surface meteorological observation stations (SMOSes) or from external data sets such as those from the Oklahoma Mesonet. For soil moisture and temperature, we consider the EBBR observations to be mostly inadequate for use in landsurface process and hydrological models or submodels. On the other hand, we expect high quality data on net radiation from EBBR stations because it is crucial in the energy balance calculations; we expect soil heat flux values to be fairly good because it enters directly into the surface energy balance calculations but is typically small in magnitude compared to net radiation. Unforeseen types of failures sometimes occur, e.g., the ventilator for one of the temperature and humidity sensors stops. Such problems are usually described in data quality reports (DQRs) that are available for data users. When the Bowen ratio is near -1, "spikes" can occur in the latent and sensible heat flux values. 8. What are likely difficulties in comparing surface heat fluxes measured by EBBR stations to results of numerical modeling efforts. One of the greatest difficulties in comparing model versus field data on surface heat fluxes is caused by model calculations requiring soil moisture information. The soil moisture across the CART site can be quite variable for summertime conditions, but CART has not been measuring it sufficiently well for many purposes. EBBR soil moisture data provide only very rough estimates of average moisture content in the top 5 cm. An effort led by Jeanne Schneider at the University of Oklahoma and supported by the National Oceanic and Atmospheric Administration for GCIP is expected to install soil moisture and temperature profiling at every CART extended facility, including every location that has an EBBR station, during early 1996. At least three science team groups have tried to compare model outputs with CART site data (as of summer 1995): Jim Liljegren working with Chris Doran at Pacific Northwest Laboratory; Marina Zivkovic working with Jean-Francois Louis at Atmos. & Environ. Research, Inc., in Cambridge, MA; and Sarah Fox working with Lee Harrison and others at the State University of New York at Albany. A cooperative program of sorts that has looked extensively at this type of modeling is PILPS (Project for Intercomparison of Land-surface Schemes). Some information on PILPS can be found in the paper by Sellers et al. (Bulletin of the American Meteorololgical Society, Vol. 74, pp. 1335-1349; 1993). One conclusion of PILPS is that more observational data is needed for developing large-scale models. For example, an article by Betts et al. (Quartery Journal of the Royal Meteorololgical Society, Vol. 119, pp. 975-1001, 1993) carries out a fairly critical evaluation of ECMWF model outputs by using FIFE data. Some other potentially informative articles are as follows: W. J. Shuttleworth, 1991: 1. Insight from Large-scale Observational Studies of Land/Atmosphere Interactions. Surveys in Geophysics, 12, 3-30. R. E. Dickinson et al., 1989: A Regional Climate Model for the Western United States. Climatic Change, 15, 383-422. R. Avissar and M. M. Verstraete, 1990: The Representation of Continental Surface Processes in Atmospheric Models. Reviews of Geophysics, 28, 35-42. 17.0 Contacts Instrument Mentor David R. Cook, Argonne National Laboratory, 9700 South Cass Avenue, Building 203, Argonne, IL 60439. Phone: (630) 252-5840, FAX: (630) 252-9792, E-mail: cook@anl.gov Vendor/Instrument Developer Radiation & Energy Balance Systems, Inc., P.O. Box 15512, Seattle, WA 98115-0512 Phone: (206) 624-7221, FAX: (206) 228-4067. 18.0 Glossary Bowen Ratio - The ratio of the sensible heat flux to the latent heat flux. Sensible Heat Flux - The transfer of sensible heat (enthalpy) between the surface and the air, or vice versa. Latent Heat Flux - The transfer of latent heat (heat released or absorbed by water) between the surface and the air, or vice versa. Net Radiation - The net difference in downwelling and upwelling solar plus terrestrial radiation. Soil Heat Flux - The transfer of sensible heat (enthalpy) in the soil, towards the surface or away from the surface. 19.0 Acronyms AEM - Automatic Exchange Mechanism BA - Bulk Aerodynamic Technique DQR - Data Quality Report EBBR - Energy Balance Bowen Ratio ECOR - Eddy Correlation System LLNL - Lawrence Livermore National Laboratory PRTD - Platinum Resistance Temperature Detector QME - Quality Measurement Experiment RH - Relative Humidity SEBS - Surface Energy Balance System SIRS - Solar and Infrared Station (Broadband Radiometers) SMOS - Surface Meteorological Observation Station VAP - Value Added Product 20.0 Citable References Field, R. T., L. Fritschen, E. T. Kanemasu, E. A. Smith, J. Stewart, S. Verma, and W. Kustas, 1992: Calibration, comparison, and correction of net radiation instruments used during FIFE. J. Geophys. Res., 97, 16681-18695. Fritschen, L. J. and L. W.Gay, 1979: Environmental Instrumentation, Springer-Verlag, NY, 216 pp. Fritschen, L. and J. R. Simpson, 1989: Surface Energy and Radiation Balance Systems: General Description and Improvements. J. App. Meteor., 28, 680-689. Halldin, S. and A. Lindroth, 1992: Errors in net radiometry: Comparison and Evaluation of Six Radiometer Designs. J. Atmos. Ocean. Tech., 9, 762-783. Heilman, J. L. and C. L. Brittin, 1989: Fetch Requirements for Bowsen Ratio Measurements of Latent and Sensible Heat Fluxes. Agr. For. Meteor., 44, 261-273. Lewis, J. M., 1995: The Story Behind the Bowen Ratio. Bull. Amer. Meteor. Soc., 76, 2433-2443. Wesely, M. W., D. R. Cook, and R. L. Coulter, 1995: Surface Heat Flux Data from Energy Balance Bowen Ratio Systems. Preprints of the Ninth Symposium on Meteorological Observations and Instrumentation, pp. 486-489, Charlotte, NC, 27-31 March 1995, Amer. Meteor. Soc., Boston, MA.