new quality control interface for rain gauges …...at a station, the qc operator can perform...
TRANSCRIPT
1. GENERAL SPECIFICATIONS
DATA ● 106 automatic rain gauges, 5-min data
(weighing and tipping bucket rain gauges)● 16 automatic rain detection sensor,
10-min data (precip. duration)● 220 manual rain gauges with daily data
→ about 33000 data/day to be controlled
→ attribute quality flags to each data• (valid, suspicious or erroneous)
→ provide estimation for missing and erroneous data
TOOLS● centralized interface for all precipitation data ● data visualization on maps● time series visualization● comparison against radar estimations● derivation of a cloud-free index from
Meteosat Second Generation (MSG) data● statistical plausibility tests
RESSOURCES● web interface● Google maps API● Oracle and SQLite databases● R+ packages (gstat, rgdal, etc.)
2. SPATIAL ANALYSISThe QC operator has the choice between various overlays in the Google maps API:
● spatial interpolation of automatic rain gauges (hourly + daily values)● spatial interpolation of manual rain gauges (daily values)● spatial interpolation of all rain gauges (daily values)● meteorological radars estimation (2 radars, hourly + daily values)● spatial interpolation of the regression residuals between
rain gauges values and radar estimates (daily values)● cloud-free index from Meteosat Second Generation, MSG (hourly values)
ABSTRACT A new interface has been recently developed at the Royal Meteorological Institute of Belgium (RMI) to support the routine daily quality control (QC) of rain gauges observations in Belgium from our centralized database. The QC interface includes various tools allowing the QC staff to highlight suspicious situations that need to be further checked. The QC procedure is thus semi-automated in the sense that the final decision to validate or to correct a value is left to the QC staff.
New quality control interface for rain gauges observations across Belgium
Michel Journée, Charles Delvaux and Cédric BertrandRoyal Meterorological Institute of Belgium, [email protected]
3. TIME SERIES ANALYSIS
At a station, the QC operator can perform various time series comparisons:
● hourly quantities against radar estimates and closest neighbors interpolation● daily quantities against radar estimates and closest neighbors interpolation● 10-min quantities against 10-min durations and 10-min average relative humidity
4. STATISTICAL QUALITY TESTSVarious types of statistical plausibility tests are performed at all time scales (5min, 1hour and 1day) before analysis by the QC operator:
● Identification of missing data● physical limits test: non-negative values + upper limit● spatial consistency test:
- comparison against a spatial interpolation of neighboring stations' values.
- special tests for isolated precipitation, isolated dryness and maintenance operations
● comparison against the estimates from the closest meteorological radar● compatibility tests between quantities and durations.
→ Quality flags (valid, suspicious or erroneous) + spatial interpolation estimations are provided for all data.
Radar estimates
MSG cloud-free indexRain gauges spatial interpolation
hourly precipitation quantities vs radar estimates and spatial interpolates
daily precipitation quantities vs radar estimates and spatial interpolates
10-min precip. quantities vs precip. duration and relative humidity