update to copc 21 november 2013 chuck skupniewicz, fnmoc, ueo co-chair yuejian zhu, emc, ueo...

Update to COPC21 November 2013

Chuck Skupniewicz, FNMOC, UEO co-chairYuejian Zhu, EMC, UEO co-chairDave McCarren, NUOPC DPM

2 NUOPCNational Unified Operational Prediction Capability

2

Agenda

NUOPC UEO Committee Update

NUOPC Verification Metrics through Oct 2013

NUOPC CMA Committee Update

Discussion

National Unified Operational Prediction Capability NUOPC 3

UEO Committee Update to COPC


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NUOPC and the North American Ensemble Forecast System (NAEFS)

Q: What’s the difference? A: Not much.

NUOPC NAEFS

Official Partners NCEP, FNMOC, AFWA

NWS, MSC, NMSM (Mexico)

Global Model Systems

NCEP+FNMOC+CMC NCEP+CMC

Parameters, Metrics and Data Standards

Same as NAEFS Same as NUOPC

Data Server NOMADS NOMADS• NAEFS focus is a coordination and sharing of research, development,

production and distribution of ensemble members for weather forecasting at each agency.

• NUOPC focus is the centralized (common) and de-centralized (mission-unique) post-processing of a multi-model ensemble products.


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Current Model Configurations


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Future Model Configurations


• Evaluate candidate NUOPC products• NCEP and FNMOC will execute reanalyses of agreed upon periods• Reanalysis will include CMC ensemble members• At a minimum reanalysis will use the NUOPC metrics

• Approve selection of NUOPC products to be made available for user access

• Approve final implementation decisions with oversight from NUOPC ESG

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According to the UEO Operational Management Plan signed by AFWA, FNMOC, and NCEP, Operational Prediction Centers will

Delivery Schedule+6:00 +7:00 +8:00 +9:00 +10:00

+6:10raw members

delivery

+7:00 Level 1Single model

products:

- L1 debiased members

- Single model statistics

+9:00 to 10:00 Level 3 multi-model products:

- group statistics-downscaled products

+8:00 Level2Multi-model

products:

- L2 group debiased members

- group statistics

Ensemble model runs completed

transmit raw

post-process, transmit L1 & statistics

transmit partners’ L2

post-process, transmit L3 downscaled products & group stats

1. “statistics” include mean, std dev, and threshold probabilities2. “group statistics” are for the multi-model ensemble3. “L1” is single model bias corrections by each center

partners’ raw

post-process, transmit L2 & group statistics

transmit partners’ L1

4 “L2” is multi-model calibration based on L1 (e.g. adjustment with NCEP analysis5. “L3” is user (or OPC) specified products based on L2 (e.g. downscaling probabilistic products)6. Partners may split responsibilities for group debiasing or statistics

Notes

Planned for 2014

Exists today


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2014 UEO Plans

All 3 agencies have agreed to a multi-month, multi-model validation during this winter using most of the agreed upon NUOPC metrics.

Each agency will share their results and make recommendations through the UEO committee. Each agency’s focus will be on statistical products most useful to their customer base.

The UEO will present consensus recommendations at the COPC spring meeting. This will include recommendation on shared production responsibilities.

COPC-approved multi-model products will be produced and distributed to the NOMADS server.

NUOPC Verification Metrics

EMC/NCEP

November 1st 2013

For all three individual bias corrected ensemble forecast (NCEP/GEFS, CMC/GEFS and FNMOC/GEFS) and combined (NUOPC) ensemble (equal weights) against UKMet analysis

Ratio of RMS error over spread

Under-dispersion

Over-dispersion

NH 500hPa anomaly correlation

NH 500hPa RMS errors

NH 500hPa CRPS skill scores

5-day forecast

Northern Hemisphere 500hPa height:

30-day running mean scores of day-5 CRPS skill scoreRMS error and ratio of RMS error / spreadAnomaly correlation

All other regions could be seen from: http://www.emc.ncep.noaa.gov/gmb/yluo/naefs/VRFY_STATS/T30_P500HGT

http://www.emc.ncep.noaa.gov/gmb/yluo/naefs/VRFY_STATS/T30_P500HGT



10-day forecast

Northern Hemisphere 500hPa height:

30-day running mean scores of day-10 CRPS skill scoreRMS error and ratio of RMS error / spreadAnomaly correlation

All other regions could be seen from: http://www.emc.ncep.noaa.gov/gmb/yluo/naefs/VRFY_STATS/T30_P500HGT




5-day forecast for surface temperature

NH RMS errors

NA RMS errorsNA CRPS skill scores

NH CRPS skill scores

10-day forecast for surface temperature

5-day forecast for surface wind (U)

10-day forecast for surface wind (U)

5-day forecast for surface wind (V)

10-day forecast for surface wind (V)

AL01-13, EP01-17, WP03-29, May-October, 2013

Forecast hoursCASES 493 448 401 356 300 206 129 81

Trac

k er

ror(

NM

)

0 12 24 36 48 72 96 1200

50

100

150

200

250

300

350

AEMN CEMN FEMN 3NCF

NA T2m


CMA Committee Update to COPC


National Unified Operational Prediction Capability NUOPC

Common Model Architecture

• Draft whitepaper sent to Liaisons for review on 4 Sep. • Being developed into BAMS article to address National

Research Council report “A National Strategy for Advancing Climate Modeling”

• Focus on advanced capability and interoperability through Earth System Prediction Suite

• ESPS is collection of Earth system component and model codes that are interoperable, documented, and available for integration and use

• ESPS implementation is part of a project awarded under ESPC entitled: An Integration and Evaluation Framework for ESPC Coupled Models

• ESPS website with draft inclusion criteria and list of candidate models (Coupled, Atmosphere, Ocean, Ice, and Wave)

http://www.earthsystemcog.org/projects/esps/

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NUOPC Layer Roadmaps• The current set of roadmaps using NUOPC Layer involves the following codes:

– Navy NAVGEM and HYCOM coupled system– Navy COAMPS coupled system– NOAA Environment Modeling System (NEMS) from NOAA NCEP EMC– NOAA Climate Forecast System (CFS) from NOAA NCEP EMC– WaveWatch 3 model from NOAA NCEP EMC and NRL– MOM5 ocean model from GFDL and CICE sea ice model from Los Alamos– GEOS-5 atmospheric general circulation model from NASA Goddard Space Flight Center– The Ionosphere Plasmasphere Electrodynamics model from the NOAA Space Weather Prediction

Center– NASA Goddard Institute for Space Studies Model E– Community Earth System Model from NCAR/DOE

• There are development pathways that traverse multiple groups, and outcomes that are interrelated– Implementing GFDL MOM5 as a NUOPC component, coupling this to a NOAA NEMS

atmosphere component, and exploring the use of this system as the architecture for the next version of CFS

– Reconciling multiple versions of the HYCOM ocean model, and using the resulting NUOPC HYCOM version in NEMS. A proposed activity would also couple this version of HYCOM to CESM.


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National Unified Operational Prediction Capability NUOPC

Common Model Architecture• ESMF v6.3.0r expected release Dec 2013• NUOPC Layer upgrades in ESMF v6.3.0r

• Developed new user orientation material with prototype codes -- http://earthsystemcog.org/projects/nuopc/

• Implemented standardization of component dependencies -- establishing a standard way for assembling NUOPC compliant components into a working application

• Implemented NUOPC Layer compliance testing tools: NUOPC Compliance Checker & NUOPC Component Explorer

• NUOPC Layer Reference and prototypes extended to include data-dependencies during initialize, standardization of component dependencies, compliance, and multi-time level coupling

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http://earthsystemcog.org/projects/nuopc/

http://earthsystemcog.org/projects/nuopc/


Questions & Discussion

The Earth System Prediction Capability (ESPC) Inter-agency Project

Phase 0: Ongoing Collaborative Programs(Operational short-range weather forecasting, research seasonal outlooks )

Inter-agency Global and Mesoscale Atmospheric Model Ensembles• Hurricane Forecast Improvement Program (HFIP: 3-7 days)• National Unified Operational Prediction Capability (NUOPC: 5-20

days)• National Multi-model Ensemble (NMME: 3-6 months)

• Multi-model Ensembles are more accurate for longer lead times. • Distributed Production Centers leverage multi-agency and

international computer infrastructure and investments.• Skill improves with spatial resolution - All are run at sub-optimal

but best affordable resolution.

Next-generation Global Atmospheric Cloud Resolving Models (GCRM) – DCMIP Candidates NMMB, FIM/NIM, Cubed Sphere, MPAS, NUMA, CAM-SE• High resolution for regional high impact and extreme events• Adaptive/unstructured mesh allows computational efficiency• Potentially Improved prediction at weather to short term seasonal

climate variability scales (5-100 days)

Phase I: ESPC Demonstrations (10 days to 1-2 years)

• Extreme Weather Events: Predictability of Blocking Events and Related High Impact Weather at Leads of 1-6 Weeks (Stan Benjamin)

• Seasonal Tropical Cyclone Threat: Predictability of Tropical Cyclone Likelihood, Mean Track, and Intensity from Weekly to Seasonal Timescales (Melinda Peng)

• Arctic Sea Ice Extent and Seasonal Ice Free Dates: Predictability from Weekly to Seasonal Timescales (Phil Jones)

• Coastal Seas: Predictability of Circulation, Hypoxia, and Harmful Algal Blooms at Lead Times of 1-6 Weeks (Gregg Jacobs)• Open Ocean: Predictability of the Atlantic Meridional

Overturning Circulation (AMOC) from Monthly to Decadal Timescales for Improved Weather and Climate Forecasts (Jim Richman)

Phase II: Decadal Prediction (5-30+ years)

The decadal to multi-decadal prediction issue is morecomplex and more focused on the forced problem and limits of predictability

• Physical – solar variability, aerosols, volcanic, albedo, glacial and sea ice melt, ocean circulation and acidification, desertification…

• Biogeochemical – ocean microbial, migrations including human, plant and animal….

• Societal – deforestation, agriculture, urbanization, industrial…

• Political – carbon limits, economic cycles, policy, water resources, warfare, …

Leverage National and International ongoing efforts in defining “operational” capability at these timescales: availability and reliability of information against decision requirements and format and mechanism for operational product generation, validation, and distribution.

Phase I: Demonstration Goals• (2013) An Implementation Plan for each Demonstration Project• (2013-2017) A better understanding of the bounds on prediction

skill at various time and space scales in the current “skill nadir” at sub-seasonal to ISI lead times for specific aspects of the earth system important to decision makers

• (2018-2022) Improved operational prediction for informed decisions (Full Operational Capability (FOC) by 2025)

The Phase I Demonstrations seek to define:• the current state of scientific understanding• the current technological approach and maturity• common skill metrics and case studies to explore areas of

predictability that could lead to future operational prediction• some measure of return on investment, i.e. computational cost

vs. prediction skill of various approaches, resolution, etc.

update to copc 21 november 2013 chuck skupniewicz, fnmoc, ueo co-chair yuejian zhu, emc, ueo...

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