The Importance of Data Quality Control inThe Importance of … · WMO RAII QM-OBS 2010.7.27 WMO RA-II (Asia) Workshop on Quality Management in Surface, Climate and Upper-air Observations

WMO RAII QM-OBS 2010.7.27

WMO RA-II (Asia) Workshop on Quality Management in Surface, Climate and Upper-air Observations

The Importance of Data Quality Control inThe Importance of Data Quality Control in Disaster Prevention and Mitigation

Kazuhiko NagataForecast Division, JMA

JMAJapan MeteorologicalAgency

Table of contentWMO RAII QM-OBS 2010.7.27

Table of content

1. Meteorological characteristics and natural disasters of Japan

2. Information for severe weather preparedness

3. Rainfall data for forecasting operations4 The importance of quality control for4. The importance of quality control for

rainfall data



Table of content




rainfall data


Japan in the Asia


Japan in the Asia

TokyoTokyo

140E135E130E


Meteorological characteristics of Japan


Meteorological characteristics of JapanSpring

Winter (Dec.-Feb.)

Baiu(Jun. – Jul.)Summer(Jul.-Aug.)( g )

Autumn


Natural disasters in Japan



Inundation

Sediment-related disasterSnow damage Examples...

High waves FloodJMAJapan

MeteorologicalAgency

High waves Flood



Natural disasters in JapanThe Number of Deaths and Missing by Type of Disaster

O 6 000Over 6,000

Reference: White Paper on Disaster Management 2009


Table of contentTable of content




rainfall data


Information delivered by JMAInformation delivered by JMA

Prefecture M i iJMA PrefecturePolice

NTT

Munici-palities

Relevant association The

general

JMA

warningAdvi-sory

MLIT(River Bureau)Fire station

Electric power company

public

Information

Electric power company

NHKMass media

Weather companyMB

SC

User

Typhoonforecast Earthquake &

volcanic information

Weather companyJM

JCG

MLIT(Civil Aviation Bureau)

User

Vessel

Plane

Marine Forecasts & Warnings

Aviation Weather Forecasts & Warnings

JMBSC : Japan Meteorological Business Support CenterNTT : Nippon Telegraph and Telephone Corporation MLIT : Ministry of Land, Infrastructure, Transport and Tourism NHK : Japan Broadcasting Corporation


NHK : Japan Broadcasting Corporation JCG : Japan Coast Guard




Heavy rain warning/advisoryHeavy Snow

Inundation

g yHeavy Snow warning/advisory

Sediment-related disasterSnow damage Examples...

Flood /

High wave

High waves秋、台風

Flood

warning/advisorywarning/advisory


High waves Flood

Information delivered by JMAInformation delivered by JMA

50 km


Criteria for heavy rain warnings/advisories WMO RAII QM-OBS 2010.7.27

and flood warnings/advisories

Amount of rainfall Sediment-related disasterFlood

Heavy Rain Warning/AdvisoryFlood Warning/Advisoryood a g/ d so y

Soil water index Runoff index


Inundation

Criteria for heavy rain warnings/advisories WMO RAII QM-OBS 2010.7.27

and flood warnings/advisoriesVisual outlines of

the soil water indexConsideration of time lag

Visual outlines of the runoff index

Rainfall accumulation in

gbetween rainfall and runoff

Consideration of time lag in flow

Storage

Runoff Drainage basin

accumulation in the drainage basin

Target

Permeation

Base rock

Runoff Drainage basin

Runoff index

area

Soil water index



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rainfall data


Precipitation observation equipment


Precipitation observation equipmentRaingauges Radar

Raingauges RadarRaingauges Radar

Advantages Can measure actual amounts of precipitation.

Can observe large areas with higher spatial resolution than the raingauge network.

Dis-advantages

Can observe precipitation at single points only.

May produce readings different from precipitation observed on the ground, as it measures the amount of rain overhead.


Precipitation observation equipment


Precipitation observation equipmentRaingauge □ JMA

□ Ministry of Land Infrastructure□ Ministry of Land, Infrastructure, Transport and Tourism(MLIT)

□ Local government

Radar

100km ● JMA△ MLIT


Radar/raingauge analyzed precipitation


Radar/raingauge-analyzed precipitation

Calibrated radar dataCalibrated radar data

Radar data

Precipita

Raingauge data

ation

Precipitation amounts observed by radar generally does not agree with those observed by raingauges, and radar data are h f lib d i h i d The calibrated radar data are then

R d /R i A l d P i it ti (R/A)

therefore calibrated with raingauge data. The calibrated radar data are then made into a single composite data set.

Radar/Raingauge-Analyzed Precipitation(R/A)Radar/Raingauge-Analyzed Precipitation data depicts precipitation with high dimensional accuracy, and is issued every thirty minutes with a spatial


and is issued every thirty minutes with a spatial resolution of 1 km.


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rainfall data


The importance of quality control for WMO RAII QM-OBS 2010.7.27

rainfall dataForecasters expect rainfall t t th t i it ito meet the trigger criteria.

Issue appropriate warning/advisoryCorrect

valuesThe general public

Forecasters may be

trust warning/advisory

yobstructed

Anomalous l Issue inappropriatevalues Issue inappropriate

warning/advisory

The general public


g pdo not trust warning/advisory

Examples of Anomalous values


Examples of Anomalous values

Inappropriate performance of raingauge inspections.g g pInfluences related to the raingauge installation siteinstallation site.Raingauge blockages.Upper data limitWrong metadataWrong metadata


Inappropriate performance of WMO RAII QM-OBS 2010.7.27

raingauge inspections

50km

Anomalous values Example of the Inappropriate Radar/raingauge-analyzed values p pp p

performance of raingauge inspections

precipitation is made automatically

If inspections are carried out correctly, such anomalous values will not arise.


Influences related to the raingauge WMO RAII QM-OBS 2010.7.27

installation site

l th th t l

10km

hi h th th t llower than the true values. higher than the true values.

Example of the Influences related

Raingauges in such locations should be moved to a suitable place or not used.


pto the raingauge installation site

Raingauge blockages


Raingauge blockages

Normal observation Funnel blocked Blockage is removed

Such anomalous values may occur at any time, so forecasters


need to judge whether or not raingauge data are correct.

Upper data limit


Upper data limit

data showing 146mm was regarded as anomalousanomalous.

10km

If upper data limit is inappropriate, data showing large amounts of rainfall may be regarded as anomalous even if they are correct

Max:110mm Max:150mm


rainfall may be regarded as anomalous even if they are correct.

Wrong metadata


Wrong metadata

10km 10km

if the location of a raingauge is wrong, even if it observes heavy rain correctly, forecasters will misidentify the location of the precipitation.


y, y p p

Conclusion


Conclusion

Quality control for observed data is important y pfor smooth forecast operation.

Follow an observation procedure and inspection dprocedure.

Select the appropriate raingauge installation site.

Decide the upper data limit carefullyDecide the upper data limit carefullyMake a correct metadata

It h ld l b t d th t th i t f litIt should also be noted that the importance of quality control for manual observation is the same as that for automatic observation.

Forecasters require accurate, prompt observation data. It is important to obtain correct measurements at fixed ptimes and report them quickly.



Thank you for your attention

EndEnd


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The Importance of Data Quality Control inThe Importance of … · WMO RAII QM-OBS 2010.7.27 WMO RA-II (Asia) Workshop on Quality Management in Surface, Climate and Upper-air Observations