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Bridging Climate Research and Operation NWS Science and Technology Infusion Plan for Climate Services NWS Science and Technology Infusion Plan for Climate.

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Presentation on theme: "Bridging Climate Research and Operation NWS Science and Technology Infusion Plan for Climate Services NWS Science and Technology Infusion Plan for Climate."— Presentation transcript:

1 Bridging Climate Research and Operation NWS Science and Technology Infusion Plan for Climate Services NWS Science and Technology Infusion Plan for Climate Services Jiayu Zhou NWS/Office of Science and Technology Updated, 14 April 2004

2 Outline I.Introduction * * II.Developing R&D Needs 1.Prediction * * 2.Modeling * * 3.Regional Services * * 4.Precipitation Data & Hydrological Science * * III.Collaboration with Strategic Partners * * IV.NWS STIP Opportunities * *

3 I.Introduction 1.Climate System * * 2.NWS Vision of Climate Services * * 3.NWS STIP Concept and NOAA Climate Matrix Management * * 4.STIP Climate Missions Identify and explore important developing S&T issues and making report and recommendation to the leadership (SPARC, CPASW, CSA, EMC/GMB Climate briefing etc.) Discuss R&D needs with scientists in operational centers and communicate the issues to the research community (NCAR, CDC, ARL, OGP, UM, GMU/COLA, FSU/COAPS etc.) Provide consultation on science issues to local forecasters. Invite distinguished researchers to address important S&T issues in S&T Seminar Series. Make decision briefing to NWS Science subcommittee, when needed. 5. 2003 Review Learning from 2002/03 winter forecast failure Identify problems ** Visit NCAR, CDC** Back

4 II.Developing Issues 1.Prediction Provide seamless suite of products and services Further improvement based on identified predictable information (El Nino, Soil Moisture, Trends * )Further improvement based on identified predictable information (El Nino, Soil Moisture, Trends * )* Forecast tools improvement * Forecast tools improvement ** Exploration of predictability beyond current knowledge *Exploration of predictability beyond current knowledge ** North American monsoon system & warm season prediction * North American monsoon system & warm season prediction ** AO/NAO, MJO predictability * AO/NAO, MJO predictability ** Predictability of week 2 forecast * Predictability of week 2 forecast ** Stratosphere and troposphere interaction * Stratosphere and troposphere interaction ** Impact of solar flux variability Impact of solar flux variability Back

5 2.Modeling Unified model strategy: To build confidence in Earth System Models used for the climate predictions, it is required that the same models should be able to simulate natural phenomenon on shorter time scales. To build confidence in Earth System Models used for the climate predictions, it is required that the same models should be able to simulate natural phenomenon on shorter time scales. It is only by validating model simulation on shorter time scales, can we be certain about their realism and believe in their credibility for making climate change projections. It is only by validating model simulation on shorter time scales, can we be certain about their realism and believe in their credibility for making climate change projections. Understanding recent model improvement and the impact on climate forecast *Understanding recent model improvement and the impact on climate forecast ** Continue to improve simulation of physics, dynamics & chemistry processes and coupling of atmosphere, ocean, land and sea ice models *Continue to improve simulation of physics, dynamics & chemistry processes and coupling of atmosphere, ocean, land and sea ice models ** Back

6 3. Regional Services Expand Climate Products and Services Regionally and Locally Regional predictability ** * Role of downscaling ** * Linking weather extreme events to climate anomalies ** Climate testbed for regional services (Example*)* R Regional climate data reanalysis Software development for regional climate services XCLIMATE - A regional climate information search engine developed by Alaska Regional Office

7 III.Collaboration with Strategic Partners III.Collaboration with Strategic Partners * * 1. 1.Seasonal Diagnostics Consortium ** 2. 2.Routine Attribution / Forecast Discussions (CPC, IRI, CDC and Others) 3. 3.OGP Supported Programs (NAME, LDAS, Etc.) 4. 4.NESDIS/NCDC and NWS Joint FY05 Initiative for Ensuring Data Continuity for Observing Systems 5. 5.Climate System Analysis 6. 6.UW Prof. Donald Johnson and NWS/NCEP Interaction ** 7. 7.NSF/NCAR Dr. Trenberth’s Recommendation * * 8. 8.Proposed NOAA Silver Spring In-house Capability of Weather-Climate Connection Assessment and Prediction Operational Development ** Back

8 IV.NWS STIP Opportunities 1.Collaborative Science, Technology, and Applied Research Program * * 2.Cooperative Program for Operational Meteorology, Education and Training (COMET) Outreach Program * *

9 NWS/CSD R. Reeves R. Reeves M. Timofeyeva M. Timofeyeva Team Composition (2002): Jiayu ZhouNWS/OSTJiayu ZhouNWS/OST Bob LivezeyNWS/OCWWSBob LivezeyNWS/OCWWS Ed O’lenicNWS/NCEP/CPCEd O’lenicNWS/NCEP/CPC Martin P. HoerlingOAR/CDCMartin P. HoerlingOAR/CDC Richard W. ReynoldsNESDIS/NCDCRichard W. ReynoldsNESDIS/NCDC Simon MasonIRI/UCSDSimon MasonIRI/UCSD Fiona HorsfallNWS/OCWWSFiona HorsfallNWS/OCWWS NWS/NCEP L. UccelliniL. UccelliniCPC J. D. LaverJ. D. Laver A. KumarA. Kumar V. KouskyV. Kousky H. M. van den DoolH. M. van den Dool W. HigginsW. Higgins D. UngerD. Unger P. XieP. Xie P. PengP. Peng E. YaroshE. Yarosh W. EbisuzakiW. Ebisuzaki W. ShiW. Shi C. LongC. Long L. HeL. He A. MillerA. MillerEMC S. LordS. Lord H.-L. PanH.-L. Pan K. MitchellK. Mitchell B. FerrierB. Ferrier D. BehringerD. Behringer Y.-T. HouY.-T. Hou S. HarperS. Harper W. WangW. Wang W. YangW. Yang R. GrumbineR. Grumbine OAR/OGP M. JiM. Ji A. BamzaiA. Bamzai R. LawfordR. Lawford J. HuangJ. Huang M. PattersonM. Patterson NWS/OHD Q. DuanQ. Duan OAR/CDC R. Dole R. Dole Acknowledgements: UW D. JohnsonD. Johnson Climate Services Observation Outreach Forecast UM E. KalnayE. Kalnay NSF/NCAR K. TrenberthK. Trenberth J. TribbiaJ. Tribbia G.MeehlG.Meehl OAR/ARL D. SeidelD. Seidel NESDIS/ORA X. Li X. Li

10 Key Products / Services Key Products / ServicesKey Products / ServicesKey Products / Services NCEP/CPC Long-Lead Forecast Tools NCEP/CPC Long-Lead Forecast ToolsNCEP/CPC Long-Lead Forecast ToolsNCEP/CPC Long-Lead Forecast Tools Climate Services Back-up Information

11 Week 2 Forecast Currently, CPC skill of day 7+ forecast is ~0. CPC week 2 forecasts are for probability of 7-day mean temperature and total precipitaton at a lead of 7 days. (Give three climatologically equally likely (terciles) categories.

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