commission for instruments and methods of observation fourteenth session geneva, 7 – 14 december...

Commission for Instruments and Methods of Observation

Fourteenth SessionGeneva, 7 – 14 December 2006

INSTRUMENTS AND METHODS OF OBSERVATION FOR SURFACE MEASUREMENTS

(OPAG Surface)

surface technology and measurement techniques

(ET-ST&MT)

22006-12-07

Major topics

• Automation of visual and subjective observations

• Information on available instrumentation and instrument development

• Measurements in harsh environments• Design, layout and representativeness of

weather stations• Urban and road meteorological measurements• EC: Cost reduction; environmental issue with

mercury

32006-12-07

Major topics

• Automation of visual and subjective observations

• Information on available instrumentation and instrument development

• Measurements in harsh environments• Design, layout and representativeness of

weather stations• Urban and road meteorological measurements• EC: Cost reduction; environmental issue with

mercury *

42006-12-07

Automation of (visual and subjective) observations

• Automation of manned observations– Low impact on instrument measurements

but: quality assurance & siting is critical– Uniform and standardized determination of

Present/Past Weather (visual & subjective observations) remains unsolved

“Observing the weather is more than measuring a set of variables”

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Quality assurance


Ref.: World Climate Data and Monitoring Programme, WCDMP-52 (GUIDELINES ON CLIMATE OBSERVATION NETWORKS AND SYSTEMS)

(Photo: Meteorological Service of Canada)

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• Lay-out of a station


Manual on the GOS: Layout of an observing station in the northern hemisphere showing minimum distances between installations (Source: UK Meteorological Office, Observer's Handbook, 4th edition, 1982)

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• Representativety


Ref.: World Climate Data and Monitoring Programme, WCDMP-52 (GUIDELINES ON CLIMATE OBSERVATION NETWORKS AND SYSTEMS)

(Photo: Meteorological Service of Canada)

• Siting & exposure

• Intercomparing MAN ↔ AUT

(Photo: Finnish Meteorological Institute, Finland)

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• Representativety

• Layout of a station

• Siting & exposure

• Intercomparing


Documented inCIMO Guide, IOM reports.

Like with instrument measurements to provide the traditional physical variables, like temperature, pressure, wind, etc.

In fact increased flexibility

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New developments (in collaboration with CBS ET-AWS):

• Definition and description of a standard AWS • Lists of basic metadata elements• Quality monitoring procedures for data from

AWS• Standardized classification scheme of

meteorological stations, taking into account the standards for siting and exposure of meteorological instruments

WMO MANUAL on the Global Observing System (WMO-No. 544)

Variables SYNOP Land

Stations

[Fixed] Ocean Weather Stations

Aeronautical meteorological

station

Principle climatological

station

STANDARD

Atmospheric Pressure M A M A X 1) X A

Pressure tendency & characteristics [M] M [A]

Air temperature M2) A M A X X3) A

Humidity5) M A M X4) X A

Surface wind6) M A M A X X A

Cloud Amount and Type M M X X A

Extinction profile/Cloud-base M [A] M X X A

Direction of Cloud movement [M]

Weather, Present & Past M M X X A

State of the Ground [M] n/a X7) [A]

Special Phenomena [M] [A]

Visibility M [A] M X X A

Amount of Precipitation [M] [A] [A] X A

Precipitation Yes/No A [A] X A

Intensity of precipitation [A]

Soil temperature X A

Sunshine and/or Solar radiation X A

Waves M [A] A8)

Sea temperature M A A8)

M = Required for manned stations, [M] = Based on a regional resolution, A = Required for automatic stations, [A] = Optional for automatic stations, X = Required

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2.1 Station information Basic station metadata include:

Type of metadata Explanation Examples Station name Official name of the station Prievidza Station index number(s) Number(s) used by the National Meteorological

Service to identify a station 11867

Geographical co-ordinates Latitude and longitude of the station reference point 18.7697 18.5939

Elevation above mean sea level Vertical distance of a reference point of the station measured from mean sea level

260.25 m

Types of soil, physical constants and profile of soil

Description of soil type below the station, its characteristics

clay

Types of vegetation and condition, the date of the entry

Description of the station’s environment land natural; grass, 7 Dec 2004

Local topography description Description of the station’s surroundings, with emphasis on topographic features that may influence the weather at the station

valley station

2.2 Individual instrument information

2.3 Data processing information

2.4 Data handling information

2.5 Data transmission information

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TECO-98 (Casablanca), IOM Report 70: Meteorological Measurement Representativety, Nearby Obstacles Influence (Michel Leroy, France).

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Automation of visual and subjective observations

However:

Assessment of the state and development of the atmosphere, and of significant weather

Remains critical, i.e.Subjective observations or qualitative data has to be converted into quantitative data or variables

To be able to generate requestedmeteorological information

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• How to register quantitatively specific weather phenomena on remote distance, like:

significant phenomena (thunder, obscuration, showers, fog patches or whirls in the vicinity)

different mixtures of precipitation types and intensities, inclusive freezing, blowing, drifting

cloudiness: not only coverage and cloud base, but also cloud type like cumulonimbus to indicate convection (e.g. CB, CTU)

• How to encode all these phenomena

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Introducing • appropriate models describing the present state of the

atmosphere• sophisticated algorithms, linking various variables

data information

physicalquantities

temperature,wind, etc.

various typesof datasources

atmosphericmodels

algorithms

weatherinformation

convert the data into information

‘easy’:uniform

‘complex’:divers

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Conversion matrix (example):

INPUT: Data

ptu fd prec.remotesensing

atm.models

OUTPUT:Information (real

time) ptu

fd

(etc)

icing, slipperiness

cloud information

phenomena

Weather

PhysicalVariables

via database

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VARIABLE 1)

Maximum Effective Range 2)

Minimum Reported Resolution 3)

Mode of Observation 4)

BUFR / CREX 5)

CLOUDS

Cloud base height 0 – 30 km 10 m I, V 0 20 013

Cloud top height 0 – 30 km 10 m I, V 0 20 014

Cloud type, convective vs. other types

up to 30 classes BUFR Table I 0 20 012

Cloud hydrometeor concentration

1 – 700 hydrometeors dm-3

1 hydrometeor dm-3 I, V N

Effective radius of cloud hydrometeors

2·10-5 – 32·10-5 m 2·10-5 m I, V N

Cloud liquid water content 1·10-5–1.4·?10-2 kg m-3 1·10-5 kg m-3 I, V N

Optical depth within each layer Not specified yet Not specified yet I, V N

Optical depth of fog Not specified yet Not specified yet I, V N

Height of inversion 0 – 1 000 m 10 m I, V N

Cloud cover 0 – 100% 1% I, V 0 20 010

Cloud amount 0 – 8/8 1/8 I, V 0 20 011

VARIABLE 1)




BUFR / CREX 5)

OBSCURATIONS

Obscuration type up to 30 types BUFR Table I, V 0 20 025

Hydrometeor type up to 30 types BUFR Table I, V 0 20 025

Lithometeor type up to 30 types BUFR Table I, V 0 20 025

Hydrometeor radius 2·10-5 – 32·10-5 m 2·10-5 m I, V N

Horizontal - extinction coefficient

0 – 1 m-1 0.001 m-1 I, V N

Slant - extinction coefficient 0 – 1 m-1 0.001 m-1 I, V N

Meteorological Optical Range 1 – 100 000 m 1 m I, V N

Runway visual range 1 – 4 000 m 1 m I, V 0 20 061

Other weather type up to 18 types BUFR Table I, V 0 20 023

VARIABLE 1)




BUFR / CREX 5)

PRECIPITATION

Accumulation 0 – 500 mm 0.1 kg m-2, 0.0001 m T 0 13 011

Duration up to 86 400 s 60 s T 0 26 020

Size of precipitating element 1·10-3 – 0.5 m 1·10-3 m I, V N

Intensity - quantitative 0 – 2000 mm h-1 0.1 kg m-2 s-1, 0.1 mm h-1 I, V 0 13 055

Type up to 30 types BUFR Table I, V 0 20 021

Rate of ice accretion 0 – 1 kg dm-2 h-1 1·10-3 kg dm-2 h-1 I, V N

ET/AWS-2006 (functional specifications)

I: Instantaneous – 1-minute value (instantaneous as defined in WMO-No.8, Part II, paragraph 1.3.2.4);V: Variability – Average (mean), Standard Deviation, Maximum, Minimum, Range, Median, etc. of samples – those

reported depend upon meteorological variable;T: Total – Integrated value during defined period (over a fixed period(s)); maximum 24 hours for all parameters except

radiation which requires a maximum of one hour.A: Average (mean) value.·


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Quality evaluation and assurance of automated subjective observations:

– ‘measurement uncertainty’ of a quantitative variable is not applicable

– ‘performance indicators’, using a contingency matrix

detectoryes no

realityyes a b

no c d

ESS: Equitable Skill ScorePOD: Probability of DetectionFAR: False Alarm Ratio

182006-12-07


Quality evaluation and assurance of automated subjective observations:

– ‘measurement uncertainty’ of a quantitative variable is not applicable

– ‘performance indicators’, using a contingency matrix

detectoryes no

reality yes 15% 5%

no 5% 75%

POD = 75%FAR = 25% acceptable?ESS = 69%

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Items to be solved:

• How to calibrate (up to source) a “multi-parameter followed by algorithm”?

• What is an appropriate (set of) reference(s) (natural – artificial; human observations are subjective)?

• Can a reference be made traceable to any standard?

• Is regional climate relevant (arctic, tropic, mountainous, deserts)?

202006-12-07

Information on available instrumentation and instrument

development1. Instrument Development Inquiry

(IDI-7 published, IDI- 8 to be issued)

2. World Meteorological Instrument Catalogue (CMA) on CD

3. HMEI* Members Product Catalogue via the Web (see INF. 9)

4. Web Portal on Development, Maintenance and Operation of Instruments, Observing Methods and AWS (CIMO homepage)

5. Other (CIMO Guide, IOM reports)

* HMEI = Association of Hydro-Meteorological Equipment Industry

OPAG CBissues

212006-12-07

Information on available instrumentation and instrument

development• Instrument Development (only) Inquiry

(now: every 4 years)(IDI- 7 published, IDI- 8 to be issued):

• IDI-reports published

– Like IDI-7 (IOM Report No. 93, WMO/TD No. 1352)

Or / and

– As Web Portal, updated regularly, to be up-to-date.

222006-12-07

Measurements in harsh environments

• Most instruments are designed for use in moderate climate zones, although requirements are valid for all climate zones.

• Special attention shall be given to– Harsh environments (arctic, tropic, desert, mountains)– Severe weather (able to survive)

Necessary actions:1. Extend of definitions and requirements on measurements

in severe weather conditions. 2. To provide recommendations for instrument development3. HMEI members are encouraged to develop ..4. Intercomparisons have to be organized for further

evaluation

232006-12-07


Source: Eumetnet Severe Weather Sensors Project no. 2

242006-12-07


• Extend of definitions and requirements on measurements in severe weather conditions:

Rec. 4.1/1:The CIMO Guide be expanded to include:

a. A definition of the siting characteristics of the Automatic Weather Station in terms of local icing conditions, and

b. The requirements for measurements in severe icing conditions.

252006-12-07

• Urban meteorology: new chapter in CIMO Guide (Urban Observations) [all scales of urban climates (micro-, local- and meso-scale) considered] + IOM rep. 81

• Road meteorology: publication of IOM rep. 71:– Need to review the use of Roadway Environmental

Stations (R-ESS),– To provide a comparison, between R-ESS and

standard synoptic meteorological stations– To examine differences between the existing and

proposed R-ESS standards

Urban and road meteorological measurements

262006-12-07

surface technology and measurement techniques (ET-ST&MT)

1. Progress in development of new technologies 2. Additional siting standards for Synoptical meteorology, Climate, Marine,

Agrometeorology, Hydrology + Urban and Roadway sensor locations 3. Standard observing methods for the automatic measurement of present

weather, clouds and weather phenomena. Optimize methods for reporting present weather, clouds and weather phenomena (in cooperation with the HMEI)

4. Evaluate the performance of AWOSs in tropics and consult manufacturers on relevant findings to propose improved designs. Advise Members on use of AWOS in extreme climatological conditions;

5. Available algorithms used in AWSs - possible standardization;6. Support to Natural Disaster Prevention and Mitigation (NDPM) in identifying how

surface-based technologies can support monitoring of natural hazards;7. Extreme weather events: encourage instrument manufacturers and others to

develop more robust instruments with greater resilience to extreme weather conditions and with increased measuring range;

8. Taking into account the environmental concerns of Members using mercury-based instruments investigate alternative solutions and advise Members;

9. Develop guidelines and procedures for the transition from manual to automatic surface observing stations.

commission for instruments and methods of observation fourteenth session geneva, 7 – 14 december...

Documents

station automation of

subjective observations

required slide

mercury slide

instrument measurements

finland slide

flexibility slide

manned stations