Table of Contents

• Introduction
• Data Access
• Location
• Sensors
• Known Instrument Problems
• Chronology
• Processing Notes
• Daily Weather Plots
• Other Plots

Introduction

Dataset Status

***** NEW: The data values were reprocessed 5 June 2000 to fix krypton hygrometer values (see below). Note that a lot of sensible heat flux values (H) are now missing, since the conversion from sonic temperature to actual temperature depends on humidity. For approximate values of H during these periods, use: rho*Cp*w'tc', where rho~1.16 g/m3 and Cp~(1006 + 1857*Q*0.001) J/kgK. *****

The 5-minute and 30-minute datasets have been corrected for:

• Tilt corrections applied to all sonic anemometer statistics (see below). (NOTE: Values involving u and v are still in boom-oriented coordinates.)
• The empirical calibration applied to the soil moisture data (see below).
• Removal of calibration events in the rain gauge data.
• Rlw.up recomputed without Tdome correction, since Tdome.up was bad. Also, some early bad pyrgeometer values removed.
• Removal of values when the krypton hygrometers were covered with plastic bags.

In addition to the corrections mentioned above, the 30-minute dataset contains:

• Specific humidity (Q) has been computed from T and RH.
• Include boom azimuth for the sonic, so all values involving u and v are now in geographic coordinates.
• The momentum, sensible and latent heat fluxes (u*, H, LE) have been computed from the sonic data using all known corrections (Webb, recover T from Tc, etc.). Note that u* is from the magnitude of u'w' and v'w', not the projection of the stress vector on the mean wind vector (which would be correct).
• The surface heat flux (Gsfc) has been computed from the soil heat flux (Gsoil) plus heat storage determined from soil temperature and moisture.
• The "oxygen correction" has been applied to LE calculated from the krypton values.

Data Access

• 5-minute averages of first and second-order moments of calibrated data, including data from all eight PAM and ASTER sites. We recommend combining these to obtain more statistically-significant averages over longer time periods (note that 30-minute averages are also available). These are available at NetCDF data files.
• 30-minute averages of first and second-order moments of selected calibrated data. Note that the second-order moments include the "variance of the means" and thus are the true 30-minute average. These 30-minute statistics are available at cases97_30min.nc.
• 1, 10, or 20 sample/second uncalibrated values from the ASTER sites. Software is maintained at RTF to generate calibrated time series on demand using the most current calibration routines, in either ASCII or floating point binary format. For access to the ASTER time series, please contact RTF.

Location

1. PAM (map): rangeland, 37deg 35.44' N, 96deg 39.10' W
2. PAM (map): rangeland, 37deg 33.11' N, 96deg 33.31' W
3. PAM (map): new corn/beans, 37deg 29' 40" N, 97deg 01.90' W
4. PAM (map): milo stubble/rangeland, 37deg 35.59' N, 96deg 57.12' W
5. PAM (map): new milo, 37deg 30.21' N, 97deg 08.38' W
6. PAM (map): winter wheat (floodplain), 37deg 16.30' N, 97deg 00.56' W
7. ASTER (map): winter wheat, 37deg 26.65' N, 96deg 59.97' W
8. ASTER (map): rangeland, 37deg 24.04' N, 96deg 56.80' W

Sensors

The PAM sites were instrumented with standard sensors and the ASTER sites were instrumented to function similar to the PAM stations. In addition, other sensors were added to the ASTER sites (see below). Generally, chemistry and spectral-resolving radiation sensors were added at site #7 and site #8 was used for testing sensors.

Since NCAR/ATD did not have enough flux sensors to instrument 8 stations, it was necessary to obtain sensors from several sources, and thus a mix of sensors was used for CASES. These were:

1. Gill sonic; krypton hygrometer
2. Gill sonic; krypton hygrometer
3. ATI sonic; krypton hygrometer
4. ATI sonic; krypton hygrometer
5. ATI sonic; krypton hygrometer
6. Gill sonic; krypton hygrometer
7. ATI sonic; OPHIR hygrometer
8. ATI sonic; OPHIR hygrometer

Soil measurements were made to characterize the first 10 cm depth. The temperature probe was inserted on a slant to average from 1-9cm. The (automatic) soil moisture probe was inserted horizontally at 5cm and its radiation pattern roughly integrates from 3-7cm. Soil moisture comparison measurements were made manually using (TRIME) probes inserted on a slant to integrate between 0-10cm and using core samples taken from 1-7cm (note that this is weighted higher than the other measurements).

Several non-standard sensors were used for this program:

• ETI rain gauges were deployed at stations #2 and #6 for comparison to the MRI rain gauges used at all other sites.
• A 4-component (visible and infrared radiation, upward and downward looking) set of radiation sensors at station #7.
• Two PAR sensors were mounted facing up and down to get a "PAR albedo" at station #7.
• A Licor carbon dioxide sensor with an inlet colocated with the sonic anemometer at station #7 for measuring CO2 fluxes.
• A fast-response surface effect chemiluminescent ozone detector with an inlet at the sonic anemometer at station #7 for measuring ozone fluxes.
• A prototype low-power surface effect chemiluminescent ozone sensor (SECLOD)near the sonic anemometer at station #7.
• A Campbell Scientific sonic anemometer at station #8 which was being evaluated as a future sensor for PAMIII.
• A prototype low-power infrared humidity sensor at station #8.
• An aspirated temperature and humidity sensor at station #8 to test our bandpass covariance method for measuring fluxes.
• A Skye Instruments "veggie" meter (possibly their SKR 110) measured radiation at 630 and 780 nm to estimate NDVI. Initially, this was deployed at station #7 to measure wheat growth. It was moved 22 Aug to station #8 and was mounted at 7m pointing about SSE, to capture the green-up of the grassland. WARNING: The variables "Rveg.660" and "Rveg.730" have from this instrument at both locations. ALSO, the data from this instrument are suspect (sometimes negative values) until further notice.

Known Instrument Problems

Rain Gauges

I will remove the jumps in the data caused by these calibrations from the final data set.

A plot of the accumulation time series for the period 18 April - 26 May is available (without any adjustments). The total accumulations (both with and without adjustments for the above calibrations) at the end of this period are shown in another table. Note that both ETI gauges read less than the MRI gauges by about 30%. (Although Ed Brandes has noted that the ETI is sometimes higher than the MRI for an individual rain event.)

Soil Moisture

Pyrgeometers

Rlw = Rpile + sigma Tcomp^4 - [1.11 sigma (Tdome^4 - Tcase^4) + 0.036 Rsw]

However, the Tdome signal from the downward-looking radiometer (measuring pyg.out) was bad, with an offset of about -8 C and noise. Since the sensor operated normally in the lab, and the A/D channel passed its check-out, the problem presumably was an electrical connection. This isn't a serious problem, since we expect Tdome to be nearly equal to Tcase for the downward-looking sensor. Thus, the Tdome^4 - Tcase^4 term above should be neglected for pyg.out.

Chronology

• 3 April: Base installed.
• 16 April: All sites reporting data.
• 22 April: Official start of operations.
• 21 May: Official end of operations.
• 28 May: Estimated end of tear-down.

Data Processing Notes

Sonic Anemometer Tilt Correction

We generate this correction by fitting to the equation: W = Wo + a*U + b*V, where U, V, W are 5-minute averages of the measured wind components and the fit is done over the entire period that the instrument was not moved. The fit is reported as an offset in W, a "lean angle" (where 0 is vertical), and a "lean direction" (where 0 is along the azimuth of the anemometer u-component). An example of this fit is given here for the CSAT anemometer.

We use one fit for the entire data set, unless we know of a discontinuity. There were only 2 such events during CASES; the u-component was readjusted (and bias might have changed) at site 3 on 21 April and the entire anemometer was raised at site 6 on 7 May. However, neither event appeared to affect the fit significantly (based on examining the time series of the fit coefficients when a separate fit was generated for each day), so only one fit was used. For a few other sites, the fit differed as a function of time, however this probably was due to limited wind directions, and data composited over the entire period had a reasonably low amount of scatter. The resulting coefficients from this process are given in a table. Note that many of the biases were rather large (about 5 cm/s), which may have been the result of preferentially locating the towers at the top of ridges.

Daily Weather Plots

The following plots summarize conditions at each station during each day of the project. Each plot covers one and a half days (0100-1300+1 CDT) and is labeled with time in GMT at the bottom and local time (CDT) at the top. The top panel displays temperature and specific humidity measured at 2m, pressure, and precipitation rates (if present). Below that is a plot of wind speed and direction measured at 10m, with dotted lines showing the directions in which flow distortion by the towers should not be a problem (there may be more). The next panel shows net radiation, and sensible and latent heat flux. The bottom panel shows the Monin-Obukhov stability parameter, z/L, the friction velocity, u*, and the Bowen ratio calculated from the flux data. Since these fluxes and derived parameters are based on smoothed, 5-minute average statistics, they should not be used quantitatively and are only shown for guidance in selecting periods to analyze further.

• Date: Station
• 17 April: #1, #2, #3, #4, #5, #6, #7, #8
• 18 April: #1, #2, #3, #4, #5, #6, #7, #8
• 19 April: #1, #2, #3, #4, #5, #6, #7, #8
• 20 April: #1, #2, #3, #4, #5, #6, #7, #8
• 21 April: #1, #2, #3, #4, #5, #6, #7, #8
• 22 April: #1, #2, #3, #4, #5, #6, #7, #8
• 23 April: #1, #2, #3, #4, #5, #6, #7, #8
• 24 April: #1, #2, #3, #4, #5, #6, #7, #8
• 25 April: #1, #2, #3, #4, #5, #6, #7, #8
• 26 April: #1, #2, #3, #4, #5, #6, #7, #8
• 27 April: #1, #2, #3, #4, #5, #6, #7, #8
• 28 April: #1, #2, #3, #4, #5, #6, #7, #8
• 29 April: #1, #2, #3, #4, #5, #6, #7, #8
• 30 April: #1, #2, #3, #4, #5, #6, #7, #8
• 1 May: #1, #2, #3, #4, #5, #6, #7, #8
• 2 May: #1, #2, #3, #4, #5, #6, #7, #8
• 3 May: #1, #2, #3, #4, #5, #6, #7, #8
• 4 May: #1, #2, #3, #4, #5, #6, #7, #8
• 5 May: #1, #2, #3, #4, #5, #6, #7, #8
• 6 May: #1, #2, #3, #4, #5, #6, #7, #8
• 7 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 8 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 9 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 10 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 11 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 12 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 13 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 14 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 15 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 16 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 17 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 18 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 19 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 20 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 21 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 22 May: #1, #2, #3, #4, #5, #6, #7, #8,
• 23 May: #1, #2, #3, #4, #5, #6, #7, #8,

Other plots

Rain

• May 8: All sites, ETI/MRI comparison
• May 14: All sites
• May 19: All sites, ETI/MRI comparison

Soil Moisture

• Apr 21 - May 16: Raw values from all sites,

Downwelling radiation

Site 1, Site 2, Site 3, Site 4, Site 5 (first part), Site 5 (entire period), Site 6, Site 7, Site 8

Roughness length

 zo <- 10*exp(-0.4*dat("Spd")/dat("u*"))
 zo[zo<1e-6] <- NA
 ineut <- abs(dat("w't'")<.01
 par(mfrow=c(3,3))
 for (i in 1:8) {
    hist(log10(zo[ineut[,i],i]),n=30)
    title(paste("#",i,"; ",round(10^median(log10(zo[ineut[,i],i]),na.rm=T),
	dig=4),sep="")) }

Site:		1	2	3	4	5	6	7	8
Cover:		range	range	crn/bns dirt	wheat	wheat	wheat	range
zo (cm)	median	0.6	0.2	0.7	1.3	0.8	5.3	1.4	0.8
zo (cm)	maxhist	1.0	0.4	0.7	2.2	4.5	7.1	7.1	2.5

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This page was prepared by Steven Oncley, NCAR Research Technology Facility