MADIS Multi-Agency Profiler Quality Control Checks
The level 1 validity checks restrict observations to falling within a TSP-specified set of tolerance limits. Wind speeds not falling within the limits are flagged as failing the QC check. The tolerances are specified as a function of pressure level, and the profiler heights are converted into pressure using the U.S. standard atmosphere calculation. The following table lists the tolerance limits:
--------------------------------------------------- Validity Checks Temp.(C) Max Wind Level(mb) Low High Speed(Kts) --------------------------------------------------- 1000 -65 60 70 850 -50 45 90 700 -50 30 120 500 -57 5 200 400 -66 -10 250 300 -72 -20 300 250 -76 -25 300 200 -78 -30 300 150 -85 -30 200 100 -95 -30 200 70 -95 -25 200 50 -95 -15 200 30 -95 -5 200 20 -95 5 200 10 -95 15 200 <10 -95 15 200
The level 2 time-height continuity check (Weber et al. 1993; Miller et al. 1994) uses pattern recognition techniques to identify winds which do not satisfy mathematical definitions of continuity in the time and height dimensions. The current profile is quality controlled by using past data in a sliding window consisting of the last 6 profiles. The algorithm is run separately on the U and V components. There are two stages to the algorithm: a pattern recognition step that is used to determine the order in which the individual points are examined, and a second step that checks the individual points for quality. The components are grouped into patterns in such a way that, from point to point within a given pattern, the values change smoothly. Bad points are then most likely to be found near pattern boundaries where, by definition, discontinuities occur. The data are checked by comparing each component with the values interpolated from neighboring winds using a least-squares linear interpolation. The neighborhood is defined as two heights above and below the target point, and two hours back in time. If a component differs more than a predetermined threshold from the interpolated value, the wind is flagged as bad. After these bad values have been eliminated, any remaining winds that are found in a pattern of smaller than eight points are also flagged as bad.
The level 2 internal consistency checks include three separate checks that look for contamination of the data from various phenomena.
*It should be noted that while the QC checks discussed here are generally applied to the form of the variable stored in the database, the QC results will also be applied to any forms of the variable that are requested by the user and are derived from the primary variable. For example, wind speed and direction will get the QC results from the checks applied to the U and V wind components.
Subjective Intervention
Two text files, a "reject" and an "accept" list provide the capability to subjectively override the results of the automated QC checks. The reject list is a list of stations and associated input observations that will be labeled as bad, regardless of the outcome of the QC checks; the accept list is the corresponding list of stations that will be labeled as good, regardless of the outcome of the QC checks. In both cases, observations associated with the stations in the lists can be individually flagged. For example, wind observations at a particular station may be added to the reject list, but not the temperature observations.
Here are the current subjective intervention lists in use at ESRL/GSD:
QC Data Structures
The MADIS QC information available for each variable includes the following QC structures: a single-character "data descriptor", intended to define an overall opinion of the quality of each observation by combining the information from the various QC checks, and for users desiring detailed information, a "QC applied" bitmap indicating which QC checks were applied to each observation, and a "QC results" bitmap indicating the results of the various QC checks.
The following table provides a complete list of the data descriptors and the bits used in the bitmaps:
-------------------------------------------- MADIS QC Information - Multi-Agency Profiler -------------------------------------------- QC Data Descriptor Values ------------------------- No QC available: Z - Preliminary, no QC Automated QC checks: C - Coarse pass, passed level 1 S - Screened, passed levels 1 and 2 V - Verified, passed levels 1, 2, and 3 X - Rejected/erroneous, failed level 1 Q - Questioned, passed level 1, failed 2 or 3 where level 1 = validity level 2 = internal, time-height consistency checks level 3 = N/A Subjective intervention: G - Subjective good B - Subjective bad Bitmask for QC Applied and QC Results ------------------------------------- Bit QC Check Decimal Value --- -------- ------------- 1 Master Check 1 2 Validity Check 2 3 Reserved 4 4 Internal Consistency Check 8 5 Reserved 16 6 Reserved 32 7 Reserved 64 8 Reserved 128 9 Reserved 256 10 Time-Height Consistency Check 512
The QC bitmask is used in the QC applied and QC result "words" returned along with the QC data descriptor. By examining the individual bits, the user can determine which checks were actually applied, and the pass/fail status of each check that was applied.
In the QC applied word, a bit value of 1 means the corresponding check was applied, a bit value of 0 indicates the check wasn't applied.
In the QC results word, a bit value of 1 means the corresponding check was applied and failed, a bit value of 0 indicates the check passed (given that the check was applied).
The "Master Check" is used to summarize all of the checks in a single bit. If any check at all was applied, this bit will be set in the QC applied word. If the observation failed any QC check, it will be set in the QC results word.
When read as decimal numbers, the different bits that are set in the bitmask are summed together. For example, a QC applied value of 515 should be interpreted as 1 + 2 + 512, meaning the validity and time-height continuity checks were applied.
References
Miller, P.A., M.F. Barth, D.W. van de Kamp, T.W. Schlatter, B.L. Weber, D.B. Wuertz, and K.A. Brewster, 1994: An evaluation of two automated quality methods designed for use with hourly wind profiler data. Ann. Geophysicae, 12, 711-724.
Technique Specification Package 88-21-R2 For AWIPS-90 RFP Appendix G Requirements Numbers: Quality Control Incoming Data, 1994. AWIPS Document Number TSP-032-1992R2, NOAA, National Weather Service, Office of Systems Development.
Weber, B.L., D.B. Wuertz, D.C. Welsh, and R. McPeek, 1993: Quality controls for profiler measurements of winds and RASS temperatures. J. Atmos. Oceanic Technol., 10, 452-464.
Last updated 16 March 2017