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GLOSS Training Workshop Course Japan Meteorological Agency May 15-26, 2006

GLOSS Training Workshop Course Japan Meteorological Agency May 15-26, 2006. Sea Level Data Processing with SLPR2 5. Filtering of Hourly Data. Filtering: Create Daily and Monthly Values. Manual Section 6. Method. Removes primary tidal energy (S1, M1, S2, M2,)

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GLOSS Training Workshop Course Japan Meteorological Agency May 15-26, 2006

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  1. GLOSS Training Workshop Course Japan Meteorological Agency May 15-26, 2006 Sea Level Data Processing with SLPR2 5. Filtering of Hourly Data

  2. Filtering: Create Daily and Monthly Values Manual Section 6 Method Removes primary tidal energy (S1, M1, S2, M2,) 119-point (5-day) Convolution Filter centered on noon Handles Gaps -demeans data over 5-day window -assigns zero to missing data -averages across gap -performs final calculation Amplitude Response of Filter: 95, 50, and 5% at 124, 60, and 40 hours -Nyquist Frequency at 48 hours; thus, minimal aliaising from tides -Primary tidal energy has response of ~0.1% (negligible)

  3. Filtering: Create Daily and Monthly Values Manual Section 6 Procedure Step 1. Ensure each year of hourly data has 12 months of data or flags If not, use \slpr2\util\FILLVM.EXE to make blocks of months of missing data flags Step 2. Run \slpr2\filt\FILTHR.EXE Step 3. Plot daily and monthly data with \slpr2\plot\PDALL.EXE and PMALL.EXE

  4. Analyzing Daily and Monthly Values Example: Puerto Armuelles, Panama

  5. Analyzing Daily and Monthly Values Manual Section 6.3 Calculate difference with neighboring station \slpr2\filt\DIFFDAY.EXE and DIFFMON.EXE Plot (\slpr2\PDALL.EXE and PMALL.EXE) - enter “diff” for start year

  6. Difference: Puerto Armuelles, Panama minus Manzanillo, Mexico suspicious

  7. Daily Data Plot for 1999, Puerto Armuelles

  8. Difference: Puerto Armuelles, Panama minus Manzanillo, Mexico 1999 Daily and Monthly Plots useful to identify reference level shifts

  9. HOTS ASSIGNMENT • Filter years of hourly files into daily and monthly values • Plot daily and monthly values • Do this for at least two stations • Run the difference program for daily and monthly data • 5. Plot the difference files

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