Operational Implementation Requirements for Canadian Meteorological Centre Data Assimilation Fusion Meeting

1. Transfer to Ops: Requirements at the Canadian Meteorological Centre Data Assimilation Fusion Meeting Downsview January 16-17, 2012 David Anselmo Air Quality Modelling Applications Section Meteorological Service of Canada Montréal, Québec David.Anselmo@ec.gc.ca

2. 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

3. 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?

4. 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)

5. 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)?

6. 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 Assimilation system

7. 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)

8. Analysis is transmitted Trial Field is generated Analysis is generated *Image courtesy CMDA/CMC Assimilation cycles at the CMC T+ 1:50 at 7:50Z Cut-offs Global cycle R106 R200 Regional cycle T+9 at 09Z T+2:30 at 02:30Z G200 G100 T+ 2:05 at 14:05Z T+ 2:05 at 14:05Z R112 R206 R100 G218 G206 R218 T+6 à 12Z T+6 at 00Z G112 G212 T+ 1:50 at 19:50Z T+2:30 at 14:30Z T+8:15 at 20:15Z R118 R212

9. 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)

10. System Readiness • System diagnostics • Monitoring of the reliability, quality, timeliness of input • Performance measures • Routine verification of quality of final products

11. 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

12. 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

13. 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

14. 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

15. Thanks! David Anselmo Air Quality Modelling Applications Section Meteorological Service of Canada Montréal, Québec David.Anselmo@ec.gc.ca

16. Extras

17. Operational Observation Data Streams

18. 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, NO Stns: 175, 165, 35, 135, 70, 5, 20, 30, 75

19. 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

20. AQHI availability – Pacific Region • Mean 6-month availability Nov 2010: 78% • Mean 6-month availability Jan 2012: ?? DRDAS

21. AQHI availability – Prairie Region • Mean 6-month availability Nov 2010: 88% • Mean 6-month availability Jan 2012: ??

22. AQHI availability – Ontario Region • Mean 6-month availability Nov 2010: 97% • Mean 6-month availability Jan 2012: ??

23. AQHI availability – Quebec Region • Mean 6-month availability Nov 2010: 93% • Mean 6-month availability Jan 2012: ??

24. AQHI availability – Atlantic Region • Mean 6-month availability Nov 2010: 84% • Mean 6-month availability Jan 2012: ??

25. 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