Sensor Performance

3D Sonic Anemometers

Tilts

click here to download a PDF of the Plot Tilts

tilt plot for EC150 at station A8

Tc Calibration

The following plots show the agreement of the sonic temperature from the speed of sound with the virtual temperature, Tc, calculated from temperature and relative humidity from the hygrothermometers and barometric pressure. For measurements where the sonic and the hygrothemometer were not at the same height, a simple linear interpolation of T and RH is done to estimate the values at the height of the sonic.  The offset and slope of the resulting fits have not been applied to the sonic temperatures.

Plots of Tc vs tc

Tc vs tc for the EC150 at station A8

2D sonic anemometers

(add table of wind tunnel results)

 

Radiometers

(Cleaning)

(Precip - remove snow, but not rain)

After SCP, March 1-April 1, 2013, the EOL CG4s were compared under the night sky to two of our CG4s calibrated at NREL traceable to WISG, and the following post calibration values were determined. The correction factor is the ratio of original/post, and was applied to the Rpile values in post-processing.

Pyrgeometer Comparison
Pyrgeometer Original cal (uV per W/m^2) Post cal Correction factor
KZ 100225, uplooking 11.28 11.12 1.014
KZ 100226, downlooking 10.81 10.76 1.005

 

Krypton Hygrometers

The kryptons were plotted alongside several other variables to collaborate data integrity. Those variables included; the leaf wetness' sensor for indications of rain/moisture, the 'kh2oV' which would drop in response to moisture on the transducers (a value below the threshold of 1.0 Volts was a good indicator), and finally the 'H2O' alongside a theoretical H2O with the relative humidity set to 100%.

 

Infrared H20/CO2 analyzers (Li7500 and EC150)

(apply krypton flags)

 

Soil Sensors

(Fixing gaps in cactus Qsoil)

(Gsoil okay?)

(TP01 okay?)

 

Tsoils

Between the 6th and 11th of October, the Tsoil values for the 'Grass' site were returning erratic data; upon closer inspection it was found that there was an unknown error in the data system that jumbled the recording of two's complement data into columns of the 'Tsoil' vector. A script was written to parse the raw data and realign it in its proper format. Using this script, the data for the sensors at the 0.6, 1.9 and 3.1cm heights was salvaged in part. No data could be found/reconstructed for the 4.4 cm sensor due to the nature of the error.

 

TRH

The temperature and relative humidity data were constrained to one another for the quality control process. Most instances of data removal were in response to moisture on the transducer (as prompted by the leaf 'wetness' sensor). Also important was the use of the 'Ifan' variable as an indicator of the TRH fan current. Values outside a threshold usually indicated instances of sensor failure and were edited as necessary.

 

Pressure: 

2 types of barometers were used for SCP -- Vaisala PTB220B and Paroscientific Model 1600 in nanobarometer mode. One nanobarometer was deployed at 5m.M at the start of the project and was damaged by the lightning strike.  We determined that its RS232 data port was blown, but were able to rewire it to use RS422.  Later, we suspected (how?) that its calibration may have shifted also due to the strike.  After SCP, Paroscientific repaired the RS232 port and recalibrated this sensor.  Another 3 nanobarometers were received during the project and installed on 9 Nov at stations 5 (new), 10 (replaced PTB220), and 1m.M (replaced PTB220).  Barometers also are included in the Li7500s at 1m.M and 2m.M and in the EC150 deployed 12 Nov at 3m at station 8.

The PTBs had pre and post calibrations done in the lab against our Paroscientific transfer standard.  The nanobarometers had recent factory calibrations (purchased in 2012) so only a post cal check was done.  The result of this check had the following differences with respect to the transfer standard:

S/N Position Difference from standard (post) (mb) Offset (mb) 
122850  5m.M 0.33  0.13
123996 A10 0.20  0.00
123997 1m.M 0.17 -0.03 
123998 A5 0.20  0.00

Post cals of all sensors will be done using the new Ruska pressure generator that we just (1 Apr 2013) received. Initial tests suggest that the transfer standard used for SCP may have been on the order of 0.2mb low, which would explain the majority of the differences seen above.

Comparison of the 5m.M and 1m.M nanobarometers show a difference of 0.18mb (after accounting for the height difference).  This is in close agreement with the post cal data that showed a difference of 0.16mb between these sensors.

PTB220 post calibration results:

S/N Position Difference from standard (Post) (mb) Comments  Offset (mb)
0001 A3   0.21 Installed 27 Sep from MFO (with no pre-cal?)    0.01
10  A8   -0.01    -0.21
6 A9   -0.05    -0.25
A10   -0.03 Replaced 9 Nov by nano   -0.23
A12    0.00    -0.20
5 A14   -0.01    -0.21
8 3m.C   -0.04     -0.24
7 1m.M   0.00 Replaced 9 Nov by nano   -0.20 
4 20m.M   -0.02    -0.22

All of these calibrations are quite close, with the exception of sensor 1 that likely had been a while since its last calibration.  Comparison of the PTB220 and nanobarometer during the swap on 9 Nov showed differences on the order of 0.1mb (1m.M) and 0.2mb (station 10).

With all this information, we get the consistent picture that the standard used for pre and post cals likely had an offset of about 0.2mb.  Taking this offset into account, the calibrations of the remaining sensors (both PTB and nano) were within 0.05mb (and many within 0.02mb) of pre-calibrations, with 2 exceptions.  The exceptions were PTB 0001, that was taken from MFO without a recent pre-cal and Nano 122850 that had been hit by lightning. 

Offsets are shown in the last column of the above tables that correct all of the data to one standard (arbitrarily taken to be the median of the most recently-calibrated nanobarometers).  These offsets will be included in the final data set.

Below is a plot of Pressure vs. (GPS-derived) Measurement Elevation for all stations before and after the PTB/Nano swap and EC-150 addition.  The departures from linear behavior likely are due to errors in the GPS data.