This summary has been written to outline basic instrumentation problems affecting the quality of the data set and is not intended to point out every bit of questionable data. It is hoped that this information will facilitate use of the data as the research concentrates on specific flights and times.

The following report covers only the RAF supplied instrumentation and is organized into two sections.  The first section lists recurring problems, general limitations, and systematic biases in the standard RAF measurements.  The second section lists isolated problems occurring on a flight-by-flight basis.  A discussion of the performance of the RAF chemistry sensors will be provided separately, as will the respective data sets.

Section I: General Discussion

1. RAF staff have reviewed the data set for instrumentation problems.  When an instrument has been found to be malfunctioning, specific time intervals are noted.  In those instances the bad data intervals have been filled in the netCDF data files with the missing data code of -32767. In some cases a system will be out for an entire flight.

2. Position Data. Both a Garmin Global Positioning System (GGPS) and a Novatel Global Positioning System (GGPS_NTL) were used as a more accurate position reference during the program.  The systems generally performed well but both systems had some selective problems.  The Novatel system provided 5 sps position data that was clean of gitter.  However, the altitude output from the Novatel was quite noisy.  By contrast, the Garmin position data deteriorated later in the project but the altitude output was mostly clear of problems.  With this in mind, it is recommended that the Novatel data be used as the position reference (GGLAT_NTL, GGLON_NTL). There may be occasional spikes or discontinuous shifts in these values due to satellite geometry and aircraft maneuvering. The algorithm referred to in (3) below also blends the GPS and IRS position to yield a best position (LATC, LONC) that generally removes the GPS spikes.

3. 3D- Wind Data. The wind data for this project were derived from measurements taken with the radome wind gust package.  As is normally the case with all wind gust systems, the ambient wind calculations can be adversely affected by either sharp changes in the aircraft's flight attitude or excessive drift in the onboard inertial reference system (IRS).  Turns, or more importantly, climbing turns are particularly disruptive to this type of measurement technique.  Wind data reported for these conditions should be used with caution.

Special sets of in-flight calibration maneuvers were conducted on VOCALS flights TF01, RF10 and RF11 to aid in the performance analysis of the wind gust measurements.  The calibration data identified a systematic bias in the pitch and sideslip parameters. These offsets have been removed from the final data set.  The time intervals for each set of maneuvers have been documented in both the flight-by-flight data quality review and on the individual Research Flight Forms prepared for each flight. Drift in the IRS accelerometers are removed using an algorithm that employs a complementary high-pass/low-pass filter that removes the long term drift with the accurate GPS reference and preserves the shorter term fluctuations measured by the IRS.

Both the GPS corrected and basic uncorrected values are included in the final data set for the purpose of data quality review.  RAF strongly recommends that the GPS corrected inertial winds be used for all research efforts (WSC,WDC,UXC,VYC,WIC,UIC,VIC). 

Note: This data set was processed using the new pressure correction factors empirically derived from comparisons against the trailing cone static pressure reference.

4. SPECIAL NOTE: RAF flies redundant sensors to assure data quality. Performance characteristics differ from sensor to sensor with certain units being more susceptible to various thermal and dynamic effects than others.  Good comparisons were typically obtained between the two static pressures (PSFDC,PSFC), the three standard temperatures (ATRL, ATRR, ATWH), three dynamic pressures (QCRC, QCFC, QCFRC), and the two dew pointers (DPT,DPB).  Exceptions are noted in the flight-by-flight summary.  The two remote surface temperature sensors (RSTB, RSTB1) generally functioned well and also showed good agreement.  The backup static pressure system showed smaller turbulent fluctuations in the signal (PSFRD) and therefore was selected as the reference pressure (PSXC) used in all of the derived parameters.   

5. Ambient Temperature Data. Temperature measurements were made using the standard heated (ATWH) and unheated (ATRR, ATRL) Rosemount temperature sensors and an OPHIR-III radiometric temperature sensor.  Performance of all three "insitu" sensors remained stable throughout the project and showed excellent agreement.  Due to its fast response, ATRR was selected as the reference value (ATX) used in calculating the derived parameters.

The OPHIR-III sensor was flown because it is not sensitive to interference from sensor wetting or icing.  Measurements are derived from near field radiometric emissions in an infrared frequency band. The integrated sample volume of the unit is designed to extend roughly 10 meters out from the aircraft.  In actual practice there appears to have been some degradation of the filters serving to limit this viewing depth.  Since the unit points out roughly horizontally, the increased viewing depth is not a problem during normal straight and level flight.  During significant right hand turns where the ROLL angle exceeds +15 degrees, however, the OPHIR temperature will be influenced by the presence of the warm sea surface in the field of view. Typical differences between ATX and OAT during these turns are around +0.1 oC.While the unit performed quite well and its output was generally well correlated to the in-situ temperature sensors, it is susceptible to in-flight calibration drift. 

The OPHIR-III sensor has a certain amount of drift, primarily associated with significant and rapid altitude changes.  To further improve the data, a loose coupled processing method is used to remove some of this drift.  The "corrected" OPHIR temperature appears in the data set as XOAT.  It is this variable that should be used for analyses purposes.  Because XOAT is not an independent, stand alone measurement, use of the OPHIR data should be strictly limited to the direct cloud penetrations where the standard sensors have a problem with sensor wetting. 

6.Humidity Data. Humidity measurements were made using two collocated thermoelectric dew point sensors and one experimental fast response hygrometer.  Although the TDL hygrometer was requested for deployment, ongoing software problems with the system prevenedt the collection of any useful data from this instrument during the project.  A comparison of the dew point sensors (DPBC, DPTC) yielded good correlation in instrument signatures during the largest portions of the flights when both instruments were functioning normally.  Under conditions where the units had been cold soaked at high altitude or experienced a rapid transition into a moist environment, both units showed a tendency to overshoot.  The DPB sensor failed during flight rf05 and remained inoperable until flight rf08.  DPTC tended to oscillate under drier conditions so DPBC was used as the reference humidity sensor (DPXC).  

Note: Even at their best, the response of the thermoelectric dew point sensors is roughly 2 seconds.  Response times are dependent upon ambient dew point depression and can exceed 10-15 seconds under very dry conditions.   

The experimental fast response humidity sensor (XUVI) provides a logarithmic response and is electrically unstable during the early portions of each flight and thermally unstable at higher altitudes. Response varied somewhat from flight-to-flight so the output was linked to the reference dew point sensor to remove large scale drift.  Typically the data are unusable for the first 15 minutes of flight.      While slightly less accurate overall, the high rate response of this system is clearly more characteristic in mapping the sudden changes in humidity associated with the VOCALS conditions. Therefore it has been used in the calculation of the derived humidity variables (RHOUV, DPUV, MRUV, RHUM, THETAE).  It is also adequate for flux calculations.

7. Radiometric Flux Data. A set of standard upward and downward facing radiometers were used to measure shortwave, ultraviolet, and infrared irradiance. It should be noted that all units are hard mounted and that none of the data have been corrected for changes in the aircraft's flight attitude. The top ultraviolet unit (UVT) developed an intermittent electrical contact during flight rf13. Problems with the unit persisted through all of flight rf14.

8. Surface Temperature Data. Heimann radiometric sensors were used to remotely measure surface temperature (RSTB & RSTB1 the surface, RSTT cloud base.   Both down looking units functioned well through out the project with RSTB being selected as the reference system for this measurement. RSTT also functioned well.  Note that when no clouds are present above the aircraft the RSTT signal will be pegged at its maximum "cold" limit of roughly -60 oC.

9. Altitude Data. The altitude of the aircraft was measured in several ways. A pressure based altitude (PALT,PALTF) is derived from the static pressure using the hydrostatic equation and normally using the U.S. Standard Atmosphere, which assumes a constant surface pressure of 1013mb and a mean surface temperature of 288 K.  The lapse rate in the tropics can differ significantly from this standard.  For the VOCALS data set, the lapse rate used in the calculation of PALT was adjusted by using a mean surface temperature of 296.15 K.

The GPS positioning systems also provide altitude readouts (GGALT & GGALT_NTL).  These outputs normally provide a fairly accurate MSL altitude based on a ellipsoid model of the Earth (WGS-84). However, during intermittent segments of each flight there were an insufficient number of satellites to provide a good GGALT measurements.   

A radar altimeter was onboard the aircraft for the project.  The unit functioned extremely well.  The standard output (HGM232)is in ft AGL.  A new variable was added (RALT) to the data set providing this measurement in m AGL

To aid the Users in choosing a common altitude to use in their analyses, RAF now calculates a ‘reference- altitude (ALTX). Due to the problems with both PALT and GGALT, ALTX was set to the radar altitude (RALT).

11.  Liquid Water Content Data. One hot wire liquid water sensor (King Probe: PLWCC1) and one optical (PVM-100: XGLWC) liquid water sensor were mounted on the C-130 for the program.  Liquid water content is also derived from the concentration and size distributions measured by some of the optical particle probes.  Most flight show excellent agreement between all of the systems.  Note that the PVM-100 also outputs droplet surface area (XGSFC) and an effective droplet radius (XGRFF).  These measurements are more problematic.  Direct comparisons between XGRFF and the mean droplet size calculations from the SPP100 (DBARF) and CDP (DBARD) cloud droplet probes vary significantly from cloud to cloud.  RAF does not recommend using the PVM-100 data from VOCALS to assess droplet size.

12. CN Concentration Data (0.01 to 3 um). The calculation of CN sized aerosol particle concentrations (CONCN) is dependent upon total particle counts (CNTS) and the measurement of sample flow (FCN,FCNC).  The internal sample flow (FCN) has been corrected (FCNC) to ambient conditions, only, and not to STP for the calculation of particle concentration. The special inlet for this measurement is not susceptible to the normal droplet splashing effects typically noted in all clouds.  RAF believes that the in-cloud measurements taken with this system are accurate and represent a good representation on interstitial CN concentrations.

Note: The location of the inlet on the aircraft and length of the tubing connecting the inlet to the counter will induce a lag in the system response to changes in particle concentration.  Based on a comparison against the wing mounted SPP200 optical probe, the lag in CONCN for the PASE experiment is 2 seconds.  The data in the production data files have been corrected for this time lag.

13. Aerosol & Cloud Droplet Sizing Data. Four PMS 1D particle probes (SPP300, SPP100, SPP200, CDP) were used on the project.  Some specific details on each of the probes are summarized below:

SPP200 - The SPP200 aerosol particle probe functioned well for most of the flights during the project. On selected flights, the unit exhibited atypically high concentrations which were attributed to a leak in the internal plumbing.  Such occurrences are noted in the flight-by-flight summary below.

The probe being flown has been modified in order to directly measure the sample flow through the instrument. These data, recorded as PFLWC_WDL, have been used in the calculation of particle concentrations to provide a more accurate measurement of aerosol concentrations. Counts in the lowest bin size were contaminated by excessive electronic noise.  Data from that channel have been removed from the calculation of total particle concentration (CONCP).  Note that the sampling range of this probe is a sub-set of the sampling range of the CN counter.  The values of CONCP should therefore always be less that the CONCN values. During cloud penetrations splashing effects can reverse this trend due to false counts in CONCP.  Due to the sampling technique employed by this probe it is not suitable for use in clouds.

SPP100(FSSP) - The project began with a modified system (SN - #109) designed to reduce droplet shattering ahead of the optics. The unit was extremely noisy in the smaller size bins requiring the 1^st 6 bins to be edited out of the overall concentration data.  While the data are considered to be acceptable they are not as good as the CDP data.  Following flight rf10 a new unit (SN - #122) was installed as a replacement.  Bead Calibrations were conducted on both probes at the time of the swap with single point post flight checks using the French "pollen" standard continuing through the end of the project.  This unit functioned well for the final 4 flights.

SPP300 - The SSP300 aerosol probe covers a range of particle sizes that bridges the gap between the true aerosols and the smaller droplets (0.3 - 20 mm).  Like all 1-D optical probes, however, the SSP300 has no way to distinguish between aerosols, ice or water.  Due to difficulties in determining the sample volume for this probe, this measurement is the least accurate of the aerosol probes.

CDP - This probe basically matches the same droplet size distribution as covered by the SPP100 probes.  A failure in the optical heaters during flights rf03 & rf04 resulted in a complete loss of data for those flights.  Beyond that problem the system functioned very well and provides the best droplet sizing data of the two systems.

14.  Precipitation Sizing Data. Two OAP probes were flown during the project.  Unit one was a standard 2D-C probe with 25 um resolution.  This system functioned well though out the entire project.  A newly modified 2D-C with 10 um resolution was added to the payload just prior to departure.  The system functioned well for the first 5 flights, but the laser failed during rf06.  We were unable to repair this unit in the field resulting in a complete loss of data for flights rf06 - rf14.

15.CVI Data Report: VOCALS (C. Twohy, 17 Jan 2009)

CVI File Variable Names in C-130 netcdf File

CVFXFLOWS Key: The number in the first column, below, is the CVFXFLOWS value in the netcdf file. The second set of values is what combination of user instruments were on CVI at that particular time period.

 1:   CVFX5C

 2:   CVFX6C

 3:   CVFX5C, CVFX6C

 4:   CVFX7C

 5:   CVFX5C, CVFX7C

 6:   CVFX6C, CVFX7C

 7:   CVFX5C, CVFX6C, CVFX7C

 8:   CVFX8C

 9:   CVFX5C, CVFX8C

10:  CVFX6C, CVFX8C

11:  CVFX5C, CVFX6C, CVFX8C

12:  CVFX7C, CVFX8C

13:  CVFX5C, CVFX7C, CVFX8C

14:  CVFX6C, CVFX7C, CVFX8C

15:  CVFX5C, CVFX6C, CVFX7C, CVFX8C

Misc: CVCWC is set to zero when the CVI is sampling as an ambient aerosol inlet (when CVINLET = 1). Also, note that the CVI cut size was increased whenever a sample was changed or user instruments were brought on or off the CVI sample line-thus CVCWC will be lower during that time time. Due to its fuselage location, the CVI also measures drizzle water w/ imperfect efficiency, so CVCWC will be higher than other probes during drizzle periods. Contact Cynthia Twohy (twohy@coas.oregonstate.edu) with questions about the CVI data or for residual nuclei size distributions not available in the netcdf file.

16. SPECIAL NOTE: Virtually all measurements made on the aircraft require some sort of airspeed correction or the systems simply do not become active while the aircraft remains on the ground.  None of the data collected while the aircraft is on the ground should be considered as valid.

Section II:  Flight-by-Flight Summary

Section III:  Updates

The LRT data was updated 6/30/2009. The following changes were made:

• Final 2D data was merged into the files.
• FInal FO3 replaced in-field FO3.
• Drexel SO2 and DMS were merged into the files.

The CO data has not yet been released. It will be released separately when available.