Transfer to Ops: Requirements at the Canadian Meteorological Centre David Anselmo Air Quality Modelling Applications Section Meteorological Service of

Transfer to Ops: Requirements at the Canadian Meteorological Centre

David AnselmoAir Quality Modelling Applications Section

Meteorological Service of CanadaMontréal, Québec

[email protected]

Data Assimilation Fusion MeetingDownsview January 16-17, 2012

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Outline

• Requirements for an operational implementation– Make the case (identify the need)– Data readiness (observations)

▪ Top 4

– System readiness

• Common challenges to ops transfers

• Advantages to going operational

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Identify Need from Program Perspective

• What? ... products are to be generated in ops

• Who? ... are (potential) clients of the products– SPCs/forecasters, Weatheroffice/general public, other

operational systems

• Why? … – Identify the benefits of the products– Does it have to be operational to realize full benefit?– What is the importance of near real-time?

• How/Where? …

will users access the products– Is development necessary?– Are other groups involved?

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Data Readiness – Top 4• Data availability

– What is source of data?▪ Are transfers to CMC already established? Can they be?▪ Would data transfer make use of existing links to CMC?▪ What are protocols for data transfer from provider?▪ Are they reasonable/acceptable to CMC?

– Bandwidth, security concerns

– What is format of data?▪ Is it new to CMC operational systems? Is there precedence?▪ Is software in place to decode this format?

– What are long term prospects wrt data availability?

▪ Longevity, continuity of observing programs

▪ Dependence on other countries (changing budgets, priorities)

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Data Readiness – Top 4• Data reliability

– Is upstream data processing supported by provider? ▪ Is it supported 24/7?

– How are unexpected outages or routine downtimes addressed?– What is normal frequency and duration of outages &

downtimes?– What is overall percentage of data availability?

▪ Is it acceptable for operational system?▪ Is it acceptable for clients (assuming a dependency develops)?

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Data Readiness – Top 4• Data quality

– What is usability of data?– What quality measures are in place at source?

▪ Quality assured data▪ Quality controlled data

– Does data arrive with pre-applied flags?– What additional measures must be applied before data can be

used operationally?▪ Must assess negative impact on downstream users from poor

quality data

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Data Readiness – Top 4

• Data timeliness– “Latency, latency, latency.”

– For many apps, if data does not arrive in time, it is essentially useless

– Define what is “late” for the intended application

▪ Concept of a cut-off

▪ For some programs T+9h, for others T+30min

Operational Near Real-Time

– Is the entire transmission system “operationally capable”?▪ Though, it need not be operational!! (Ex. satellite)

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Assimilation cycles at the CMC

G200

G218

G212

G206 R112

G100

G112

R206R218R100

Analysis is transmitted

Trial Field is generated

Analysis is generated

T+9 at 09Z

T+6 à 12ZT+6 at 00Z

T+8:15 at 20:15Z

T+2:30 at 02:30Z

T+2:30 at 14:30Z

T+ 2:05 at 14:05Z

T+ 2:05 at 14:05Z

Global cycle

Regional cycleR200R106

T+ 1:50 at 7:50Z

R118R212

T+ 1:50 at 19:50Z

*Image courtesy CMDA/CMC

Cut-offs

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System Readiness• Applies to applicant system as well as host environment

• CPOP considerations (Comité des passes opérationelles et parallèls)

– Advance planning▪ Resource allocations (human & computer)▪ Balance/coordination with other implementation requests▪ Initial proposal 12-18 months in advance

– Coordination with existing operational components▪ Impacts & dependencies between upstream & downstream systems

– Ex. Global model, Regional model, AQ model, UMOS, OA, etc

▪ Regional SPCs (forecast scheds), Weatheroffice, etc

• Commonality of working environment (tools)– Research Development Operations

– To reduce AMAP duplication of work; streamline implementations

– Ex. Job sequencer (OCM/Maestro)

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System Readiness

• System diagnostics– Monitoring of the reliability, quality, timeliness of input– Performance measures

▪ Routine verification of quality of final products

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System Readiness

• Documentation– Creation of standards for evaluation and future upgrades

▪ What are conditions for implementations?– Define procedures for future parallel runs (seasons, length of time, etc.)– Verification scores & thresholds– Against observations/analyses– Subjective evaluations by A&P

▪ Identify dependant systems that must undergo impact assessments with every implementation

– Support documentation▪ Assist 24/7 support teams (NetOps, CMOI, A&P)

▪ Problem scenarios & remedy procedures

▪ Contingencies for data or system outages

– GENOT, Technical note, CMC product guide

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System Readiness

• Outreach– Presentation to CMC building prior to formal CPOP proposal

▪ Present in detail the science and implementation plans

▪ Present future directions

▪ 50 minutes

– Formal CPOP proposal for parallel run▪ Brief summary of science and implementation plan

▪ 15-20 minutes

▪ Voted on by CPOP members

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Common Challenges to Ops Transfers

• Each implementation = additional cost– Competition for limited resources

• The first implementation is resource intensive– Often requires significant adaptation to conform to operational

expectations▪ New data types & formats & paradigms

– Tests communication links between R, D, and O

• Maturity or lack thereof of component(s)– Observation infrastructure, robustness of methodology, etc.

• Increased complexity for assimilation systems– Marriage of 3 components: observations, model, methodology

• Adaptation to continual evolution of…– Computing environment

– Upstream/downstream systems

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Advantages to Ops Status

• Demonstrates important value/purpose of system

• Provides continuous monitoring to identify issues with data

– Quality, timeliness, etc.– In turn, opportunities to improve data stream (feedback to data

providers)

• Improves product availability & visibility

• Can be supportive to other operational systems– Ex. sensitivity of GEM-MACH has proven an effective means of

debugging dynamics & physics libraries shared by other models

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Thanks!

David AnselmoAir Quality Modelling Applications Section

Meteorological Service of CanadaMontréal, Québec

[email protected]

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Extras

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Operational Observation Data Streams

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Surface Obs Data Transfer – Canada• Source networks for surface data:

– Metro Vancouver (DRDAS)– BC MoE (DRDAS)– Alberta Env (9 air sheds, CASA server)– Saskatchewan Env (DRDAS)– Manitoba Conservation (moving to DRDAS)– Ontario MoE (DRDAS)– Ville de Montréal & Québec MDDEP (via Québec Region)– New Brunswick, PEI, Nova Scotia, Newfoundland (via Atlantic

Region)– CAPMoN

• Hourly observations

• Species: O3, PM2.5, PM10, NO2, SO2, H2S, TRS, CO, NOStns: 175, 165, 35, 135, 70, 5, 20, 30, 75

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Surface Obs Data Transfer – Canada• Format: AIRNow ‘OBS’ ASCII

• Processed in near real-time at 40 mins past hour

• Used to feed:– AQHI national forecast program– UMOS– Model verification– Objective analysis system for surface pollutants

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AQHI availability – Pacific Region• Mean 6-month availability Nov 2010: 78%

• Mean 6-month availability Jan 2012: ??DRDAS

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AQHI availability – Prairie Region• Mean 6-month availability Nov 2010: 88%

• Mean 6-month availability Jan 2012: ??

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AQHI availability – Ontario Region• Mean 6-month availability Nov 2010: 97%


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AQHI availability – Quebec Region• Mean 6-month availability Nov 2010: 93%


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AQHI availability – Atlantic Region• Mean 6-month availability Nov 2010: 84%


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Surface Obs Data Transfer – US• US obs retrieved from AIRNow Gateway

– www.airnowgateway.org

– Data in ‘AQCSV’ ASCII format

– Improvement over previous ‘OBS’ format

• Hourly observations

• Species:– Primarily O3 and PM2.5

– Includes other pollutants and meteorology for select stations

• Availability of data in near real-time:– ~80% after 1 hour

– ~95% after 2 hours

• Used to feed:– Model verification

– Objective analysis system for surface pollutants

Documents

Transfer to Ops: Requirements at the Canadian Meteorological Centre David Anselmo Air Quality Modelling Applications Section Meteorological Service of