Bridging Climate Research and Operation

NWS Science and Technology Infusion PlanNWS Science and Technology Infusion Plan

for Climate Servicesfor Climate Services

NWS Science and Technology Infusion PlanNWS Science and Technology Infusion Plan

for Climate Servicesfor Climate Services

Jiayu ZhouJiayu Zhou

NWS/Office of Science and TechnologyNWS/Office of Science and TechnologyUpdated, 14 April 2004Updated, 14 April 2004

OutlineOutline

I.I. Introduction Introduction

II.II. Developing R&D NeedsDeveloping R&D Needs

1.1. Prediction Prediction

2.2. Modeling Modeling

3.3. Regional Services Regional Services

4.4. Precipitation Data & Hydrological Science Precipitation Data & Hydrological Science

III.III. Collaboration with Strategic Partners Collaboration with Strategic Partners

IV.IV. NWS STIP Opportunities NWS STIP Opportunities

I.I. IntroductionIntroduction

1.1. Climate System Climate System

2.2. NWS Vision of Climate Services NWS Vision of Climate Services

3.3. NWS STIP Concept and NOAA Climate Matrix Management NWS STIP Concept and NOAA Climate Matrix Management **

4.4. STIP Climate MissionsSTIP 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.

5.5. 2003 Review2003 Review

Learning from 2002/03 winter forecast failure

Identify problems

Visit NCAR, CDC*

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II.II. Developing IssuesDeveloping Issues

1.1. PredictionPrediction

Provide seamless suite of products and services

• Further improvement based on identified predictable Further improvement based on identified predictable information (information (El Nino, Soil Moisture, Trends El Nino, Soil Moisture, Trends ))

Forecast tools improvement Forecast tools improvement

• Exploration of predictability beyond current Exploration of predictability beyond current knowledge *knowledge *

North American monsoon system & warm season North American monsoon system & warm season prediction 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 variabilityImpact of solar flux variability

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2.2. ModelingModeling

Unified model strategy:Unified model strategy:

To build confidence in Earth System Models used To build confidence in Earth System Models used for the climate predictions, it is required that the for the climate predictions, it is required that the same models should be able to simulate natural same models should be able to simulate natural phenomenon on shorter time scales. phenomenon on shorter time scales.

It is only by validating model simulation on It is only by validating model simulation on shorter time scales, can we be certain about their shorter time scales, can we be certain about their realism and believe in their credibility for making realism and believe in their credibility for making climate change projections.climate change projections.

• Understanding recent model improvement and Understanding recent model improvement and the impact on climate forecast the impact on climate forecast **

• Continue to improve simulation of physics, Continue to improve simulation of physics, dynamics & chemistry processes and coupling dynamics & chemistry processes and coupling of atmosphere, ocean, land and sea ice models of atmosphere, ocean, land and sea ice models

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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*)

• RRegional climate data reanalysis

• Software development for regional climate services

XCLIMATE - A regional climate information search engine developed by Alaska Regional Office

III.III. Collaboration with Strategic Partners Collaboration with Strategic Partners

1. Seasonal Diagnostics Consortium

2. Routine Attribution / Forecast Discussions (CPC, IRI, CDC and Others)

3. OGP Supported Programs (NAME, LDAS, Etc.)

4. NESDIS/NCDC and NWS Joint FY05 Initiative for Ensuring Data Continuity for Observing Systems

5. Climate System Analysis

6. UW Prof. Donald Johnson and NWS/NCEP Interaction

7. NSF/NCAR Dr. Trenberth’s Recommendation

8. Proposed NOAA Silver Spring In-house Capability of Weather-Climate Connection Assessment and Prediction Operational Development *

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IV.IV. NWS STIP OpportunitiesNWS STIP Opportunities

1.1. Collaborative Science, Technology, and Applied Collaborative Science, Technology, and Applied Research Program Research Program

2.2. Cooperative Program for Operational Meteorology, Cooperative Program for Operational Meteorology, Education and Training (COMET) Outreach Education and Training (COMET) Outreach Program Program

NWS/CSDNWS/CSD

• R. ReevesR. Reeves

• M. TimofeyevaM. Timofeyeva

Team Composition (2002):Team Composition (2002):• Jiayu ZhouJiayu Zhou NWS/OSTNWS/OST

• Bob LivezeyBob Livezey NWS/OCWWSNWS/OCWWS

• Ed O’lenicEd O’lenic NWS/NCEP/CPCNWS/NCEP/CPC

• Martin P. HoerlingMartin P. Hoerling OAR/CDCOAR/CDC

• Richard W. ReynoldsRichard W. Reynolds NESDIS/NCDCNESDIS/NCDC

• Simon MasonSimon Mason IRI/UCSDIRI/UCSD

• Fiona HorsfallFiona Horsfall NWS/OCWWSNWS/OCWWS

NWS/NCEPNWS/NCEP

• L. UccelliniL. Uccellini

CPCCPC

• 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. Peng P. Peng

• E. YaroshE. Yarosh

• W. EbisuzakiW. Ebisuzaki

• W. Shi W. Shi

• C. LongC. Long

• L. HeL. He

• A. MillerA. Miller

EMCEMC

• S. LordS. Lord

• H.-L. PanH.-L. Pan

• K. MitchellK. Mitchell

• B. FerrierB. Ferrier

• D. BehringerD. Behringer

• Y.-T. Hou Y.-T. Hou

• S. HarperS. Harper

• W. WangW. Wang

• W. YangW. Yang

• R. GrumbineR. Grumbine

OAR/OGPOAR/OGP

• M. JiM. Ji

• A. BamzaiA. Bamzai

• R. LawfordR. Lawford

• J. HuangJ. Huang

• M. PattersonM. Patterson

NWS/OHDNWS/OHD

• Q. DuanQ. Duan

OAR/CDCOAR/CDC

• R. DoleR. Dole

Acknowledgements:

UWUW

• D. JohnsonD. Johnson

Climate Services

ObservationO

utre

ach

Forecast

UMUM

• E. KalnayE. Kalnay

NSF/NCARNSF/NCAR

• K. TrenberthK. Trenberth

• J. TribbiaJ. Tribbia

• G.MeehlG.Meehl

OAR/ARLOAR/ARL

• D. SeidelD. Seidel

NESDIS/ORANESDIS/ORA

• X. LiX. Li

• Key Products / Services

• NCEP/CPC Long-Lead Forecast Tools

Climate Services Climate Services Back-up InformationBack-up Information