| INSTRUMENT MENTOR MONTHLY SUMMARY REPORT |
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Return to a list of available ECOR summariesIMMSNo 3290 loaded
| Source: ECOR | Report Date: 05/2009 |
Instrument Mentor Monthly Summary Report for ECOR: 05/2009
1. Data Review:
Please see Section 6.3 Data Assessments by Site Scientist/Data Quality Office in the ECOR Handbook (at www.arm.gov/instruments/instrument.php?id=ecor), under Common Conditions Reflecting Correct or Incorrect Data, Wind Direction Dependencies, for data validity dependence on wind direction.
Some common conditions that will be noted in the ECOR data are:
a) Periods of precipitation, fog, and dew (frost) often cause incorrect water vapor and carbon dioxide measurements. This is caused by water lying on the lower window of the LI-7500 CO2/H2O sensor, thereby obstructing the passage of the sensing IR radiation (very light precipitation may have little or no effect). The CO2 portion of the instrument is more sensitive to this condition, so it is not unusual for latent heat flux to be good, even though the CO2 flux is not. I do not write DQRs or indicate time periods in the monthly report for this wetting condition, as it would be overly time-consuming. The data user should look at co-located or nearby SMOS rain gages or the HandS ECOR plots to determine times of precipitation and you can assume that offscale or spiked readings in the few hours before dawn are often caused by dew or frost on the CO2/H2O sensor. I have written ECR 00536 to add a wetness sensor to the ECOR to provide more timely information on wetting conditions.
b) The CO2 mean sometimes flattens out during the daytime (see E24, 08/01/05 and 08/31/05).
c) Large spikes (positive and negative) in CO2 flux can occur when the flux is essentially zero (see E16, 08/16/05, 0800-0930 GMT).
d) ECOR time stamps are for the beginning of the half hour, whereas those for the SMOS and EBBR are for the end of the half hour. Therefore, when comparing data for these systems (such as on HandS plots), the values for the ECOR show a half hour earlier than the commensurate values for the SMOS and EBBR.
e) Friction velocity (ustar) and momentum flux (k) are often flagged during light wind conditions. This is normal, as these measurements, as well as the fluxes of sensible heat flux (h), latent heat flux (lv_e), and CO2 flux (fc) cannot be trusted
because of the lack of ability of the sonic anemometer to measure properly during
very low wind speeds (especially < 1 m/s).
f) Momentum flux and friction velocity have opposite signs, and mirror each other since friction velocity is computed from momentum flux; in the HandS plots they are plotted to scales with opposite sign orientations, so they trend together.
g) Plots of water vapor flux (lv_e) and CO2 flux (fc) normally mirror each other: in the HandS plots they are plotted to scales with opposite sign orientations, so they tend to trend together.
h) On rare occasions the flag for elev (angle of attack of the wind) is exceeded, normally on the positive side. The flag limits for elev are quite generous; this was done to try to accommodate the large angles that can occur at the forested Okmulgee site E21. However, the angles at the Okmulgee site can often be much larger than the qc limits because of the very uneven height of trees in the mixed deciduous forest at Okmulgee.
i) Fluxes of CO2, sensible heat, and latent heat at E21 Okmulgee forest are often larger than at other sites, particularly the fluxes of water vapor and CO2; the latter will often be twice what it is at the other ECOR sites.
j) The plots of data from the forest site at Okmulgee show more “jumping around” of the data than is seen at the other ECOR sites; this is expected and normal since the scale of eddies that carry the flux information over the tree structure is much larger than over grassland or crops.
k) When the LI-7500 CO2/H2O serial datastream is not available (pressure and temperature missing), default values are used in the calculation of the CO2 and latent heat fluxes; when default values are used, resulting errors in the fluxes are within the +/- 10% system error.
l) Sudden shifts in wind direction are not handled well by the ECOR coordinate transform routine, often resulting in a spike in each of the fluxes for a half hour measurement period.
m) When the LI-7500 or data acquisition system serial port is damaged, “garbled data” occurs. The datastream from the sonic anemometer to the data acquisition system is typically too short and can not be interpreted by the ECOR software. Fluxes are usually incorrect or offscale and CO2 and H2O densities, temperature, and pressure are often incorrect also.
n) The u and v directions of wind speed are not according to meteorological standards. For the ECOR, +u is for winds from the south and +v is for winds from the east. See Section 5.1.5 of the ECOR Handbook for more details.
o) Wind direction dependency of the flux data is shown in the ECOR Handbook section 6.3 Data Assessments by Site Scientist/Data Quality Office at subheading, Common Conditions Reflecting Correct or Incorrect Data, at item 4. The vegetation surfaces and corresponding wind directions over which the fluxes have been measured are listed; wind directions that are not listed are directions for which the fetch is insufficient and therefore for which the ECOR flux data are suspect.
p) The fluxes are typically underestimated by 10% to 25% in the ECOR half hour datastream because some corrections have not been applied to the data and
because there are inadequacies in the eddy covariance measurement technique that tend to result in underestimated fluxes. The reasons for the flux underestimates are explained in section 5.3 User Notes and Known Problems in the ECOR Handbook. Development of an ECOR VAP is in process to make corrections to the flux data in a post-processing mode, but this may not eliminate all measurement-technique-dependent flux underestimates.
Beginning in FY2006, Data Quality Reports are not written for missing data or for situations when qc flags clearly show that the data is incorrect (this is true for most of the conditions listed above). DQRs are written for periods when data is incorrect, when the situation is not represented by qc flags in the data, and it’s not obvious that the data should have been flagged as incorrect.
E1: Data quality good, except during precipitation and dew/frost. Water vapor density is about 40% greater than the SMOS.
E3: Data quality good, except during precipitation and dew/frost.
Water vapor 50% larger than SMOS on 05/19.
E5: Data quality good, except during precipitation and dew/frost.
Data missing 05/01 0000 GMT - 05/06 1700 GMT.
E6: Data quality good, when available, except during precipitation and dew/frost.
Data missing 05/08 1030 GMT - 05/14 1930 GMT.
E10: Data quality problems.
Data missing 04/29 2100-2330 GMT.
CO2 and H2O analog data incorrect 05/101 0000 GMT - 05/02 2100 GMT, 05/16 1000 GMT - 05/18 1730 GMT; CO2 and latent heat fluxes incorrect.
E14: Data quality good, when available, except during precipitation and dew/frost.
Data missing 05/10 2130 GMT - 05/11 1600 GMT, 05/19 2130 GMT - 05/20 1500 GMT.
E16: Data quality good, except during precipitation and dew/frost.
E21: Data quality good, except during precipitation and dew/frost.
E24: Data quality good, except during precipitation and dew/frost.
AMF: Data quality problems.
Apparent lack of water vapor sensitivity.
Wind direction 21 degrees high 05/01 0000 GMT - 05/08 0815 GMT.
2. Instrument Performance Issues and Trends:
3. Current Task Status:
ECO 00536 Add Wetness Sensor to ECOR. A wetness sensor was installed in an ECOR system at Fermi National Accelerator Laboratory in January 2007 for testing. Testing indicates that different phases of water and types of dew/frost/precipitation produce different voltage levels from the wetness sensor. Changes to the ECOR programming have been completed and have been successfully tested on the new AMPRO SBC.
ECR 00633 Revision of ECOR programming. Some fundamental changes to the way configurations are performed and error statements are produced would simplify some procedures and allow easier error checking. Tim Martin of ANL has finished this work.
AMF ECOR
ECOs 00536, and ECRs 00633 also apply to the AMF ECOR.
4. Near-Term Plans:
Add wetness sensor to E14 ECOR to test (see ECO-00536).
Develop an ECOR VAP to correct the flux data for density, sensor separation, and response time corrections; these corrections are not made to the data placed in the archive, resulting in overestimated CO2 fluxes in particular.
SGP ECOR
Evaluate sonic temperature versus temperature measured by a co-located SMOS and/or EBBR.
AMF ECOR
(see All ECORs section above)
5. Accomplishments:
Writing of the ECOR VAP continues.
AMF ECOR
none