Quality Control for the World Ocean Database

GSOP Quality Control WorkshopJune 12, 2013

Purpose• Define aim of quality control for the World Ocean

Database (WOD)

• Brief outline of quality control procedures for data in the WOD.

• Active areas of investigation into quality control checks.

• Presentation of quality control flags to users.

Aim of Quality Control in WOD• WOD is the input data for the World Ocean Atlas (WOA)

climatology series.

• Quality control of WOD aims at producing the definitive long-term mean gridded ocean fields.

• Quality flags represent pass/fail of a given set of tests, not good/bad judgement.

• WOD with quality flags are presented to ensure reproducibility of WOA

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Quality Control Step 0: Check for format errors, duplicate data, incorrect units, incorrect metadata.

Red: Mar. 11, 1961, 21:00GMT, 150.020°E, 41.39°NGreen: Mar. 11, 1961, 12:30GMT, 150.033°E, 41.65°N

Z (m) 0.0 10.0 30.0 50.0 75.0

Temp 11.1 11.1 1.2 1.2 1.1

Temp 1.1 1.1 1.2 1.2 1.1

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Quality Control Step 1: Automatic Checks - reveal systematic errors in incoming data and metadata - eliminate most non-representative data from consideration

Eliminates ~3% of temperature measurements from consideration.

Checks include:Range checkSpike checkDensity inversionSpeed check (no flag)Land/ocean bottom check

(no flag)Standard deviation

Profiles ( x 105)

Dep

th (m

)

Example of data flags in WOD not being used

A user showed this T-S plot as an example of problems in WOD. The vertical lines centered on S=36.5 is clearly not a feature of the real ocean.

However, when we tried to reproduce the plot on the bottom left we foundthe user had included data that we had flagged as being erroneous.

Bottle data for WMO Sq.7306 30-40°N, 60-70°W

Red: Apr. 23, 2002, 06:22GMT, 150.387°E, 36.645°SGreen: Apr. 23, 2002, 05:22GMT, 150.387°E, 36.645°S

Dep

th (m

)

Temperature (°C)

Keep all data withflags

Choices for Disseminating Quality Controlled Data

Provide only realistic data

XBT example:Two datasets, same data, different choices for disseminating quality control information

Dashed line: start of qc flag “bad” for red data.Green “bad” data removed.

Red: Apr. 23, 2002, 06:22GMT, 150.387°E, 36.645°SGreen: Apr 23, 2002, 05:22GMT, 150.387°E, 36.645°S

Dep

th (m

)

Temperature (°C)

Keep all data withflags

Choices for Disseminating Quality Controlled Data

Provide only realistic data

XBT example:Two datasets, same data, different choices for disseminating quality control information

Dashed line: start of qc flag “bad” for red data.Green “bad” data removed.

Gross Range Checks by areas [basins/latitude belts/coastal]Additional areas: Sulu Sea NW Pacific, Japan Sea, Yellow Sea, Seto Inland Seas

How narrow to make range envelopes?

Too narrow = throw out good but anomalous data.

Too wide=keep too many bad data

[At least one measurement flagged in 178,041 temperature profiles – 1.6%]

Excessive Gradient and Inversion Checks

Excessive Gradients – an excessive decrease in value over depth Temperature: 0.7°C/m [523,934 profiles, 4.8%] Excessive Inversion – an excessive increase in value over depth Temperature: 0.3°C/m [269,500 profiles , 2.5%]

Combination (spike) – excessive gradient followed by excessive inversion or vice versa. Temperature: [20,536 profiles, 0.2%]

(Also monotonic/zero value profile checks)

Quality control checks after interpolation to standard levels:

515,885 temperature profiles completely eliminated from use (4.7%)

1,156051 profiles withat least one level flagged (10.6%)

Green -> standard deviation outliers (>= 2 in a profile)Yellow -> density inversion (>=2 in a profile)Red/orange -> individual measurements/profiles/cruises subjectively flagged

Density Inversion Check: Sufficiently large negative stability between adjacent standard levels. >=2 in a single profile flags entire profile lower depth < =30 m instability > 3 x 10-5 g/cm3

lower depth > 30m <= 400m instability > 2 x 10-5 g/cm3

lower depth > 400m instability > 10-6 g/cm3

Standard deviation outlier check: >= 2 in a single profile flags entire profile

Means and standard deviations in 5° lat/lon boxesCoastal: Outlier > 5 standard deviations from mean above 50 mNear Coastal: Outlier > 4 standard deviation from mean above 50mNear bottom: Outlier > 4 standard deviations from meanOpen Ocean: Outlier > 3 standard deviations from mean

Coastal=adjacent to designated land box (1° grid) Near coastal= 2 grids from designated land box or <=200m depthNear bottom: last standard depth above ocean bottomOpen Ocean=all other ocean grid boxes

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Quality Control Step: Climatologies

Climatology afterAutomatic quality control

January temperature at 800m depth

Final Climatology

REXAMINATION OF QUALITY CONTROL PROCEDURES AT NODC BASED ON RESULTS

USING ARGO DATA

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•Extensive and intensive quality control work done Argo profile data by Data Assembly Centers (DAC)

•Additional quality control work done upon arrival of data at NODC

•What are the effects of Argo quality control and NODC quality control on ocean heat content calculations?

•Based on work done by Mathieu Hamon [PhD thesis] with Karina von Schuckmann and Gilles Reverdin [heat content discrepancy in southern hemisphere using WOD05 + Argo qc data vs WOD09 with NODC qc Argo data]

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YEAR 2009 0-700 m OCEAN HEAT CONTENT ANOMALY (OHCA) RELATIVE TO WOA09

ABOVE: FULL NODC QUALITY CONTROL

BELOW: ARGO QC FLAG 4 ONLY

ABOVE: NODC QC OHCA MINUS ARGO QC FLAG 4 OHCA

RED=POSITIVE OHCABLUE=NEGATIVE OHCA

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1985 [5%] 2009 [22%]

Global Subsurface Temperature Coverage: 60S to 30S compared to Global Ocean

Profiles with Two or More Depth Levels with Temperature Standard Deviation Outliers:

Global Ocean compared to 60S – 30S latitudes.

Left Panel: Number of ProfilesRight Panel: Percent of Total Profiles

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Float 5900242 – Cycle 25September 9, 200350.3°S, 140.5°EBlack line=Temperature profile

World Ocean Atlas Annual Mean Temperature Climatology at 600 m depth.Solid Grey Line=5° mean temperature. Dashed Grey Lines=Mean ± 3 x Standard Deviation

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•One possibility: standard deviation check is flagging too many good data

•New more inclusive climatology (WOA13), shorter time period climatology (WOA13) or float-only climatology (Roemmich and Gilson) may help

•Change or remove check

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•Second possibility: standard deviation check flagged data represent limited time/space features and should not be used for OHCA calculation

•Continue as before

•Change checks for known frequent anomalous regions (Agulhas retroflection/rings) and anomalous time periods (1997-98 El Niño/La Niña)

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Presentation of quality control flags for WOD

•WOD qc flags represent pass/fail of given set of tests

•Originators flags also included in WOD – passing on previous quality information

•For WOD13, there will be an option for IODE standard flag scheme: two flags 1) WOD pass/fail qc flag 2) IODE good/bad flag based on 1)

Summary

1. Many non-standard quality control tests/decisions are made during conversion/upload to WOD.

2. About 3% of all measurements are flagged in WOD automatic qc process.

3. Important to decide whether to present all data with flags, or remove obviously bad data.

4. > 80% of all quality control flags in WOD are standard deviation outliers. This procedure needs to be examined/changed.

5. Subjective checks important: for specific purpose or general?

6. Important to decide how to present quality control flag information