1 The Proposed Next-Generation NCEP Production Suite EMC Senior Staff January 2007 NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems

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The Proposed Next-Generation

NCEP Production SuiteEMC Senior Staff

January 2007

NCEP Production SuiteWeather, Ocean & Climate Forecast Systems

Version 3.0 April 9, 2004

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NCEP Production SuiteWeather, Ocean, Land & Climate Forecast Systems

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Overview

• Preparing for the future• Production Suite: Conceptual

prototype• Benefits• Summary

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Preparing for the Future (1)

• Improved forecast services– Greater focus on high-impact events– Additional environmental information service responsibilities– Provide more information to users and access to more info

• Support forecast offices– Efficient Grid Initialization (e.g. SmartInit)– Analysis of Record (and RTMA)– Probabilistic and ensemble methods

• Respond to external (NRC) reports– “Completing the Forecast” – “Fair Weather”

• Respond to NOAA Science Advisory Board reviews– Ocean modeling (National “backbone”)– Hurricane intensity (ensemble-based system)

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Preparing for the Future (2)

• Observations (number and availability)– Advanced Polar and Geostationary sounders (~100 X greater)

• NPOESS (<60 minutes globally) – 2012-2015 (or later)• METOP (1-4) – 2007 • NPP (90-120 minutes globally) – 2009• GOES-R – 2013 (or later)

– Next-generation Doppler radar• Advanced post-processing techniques for multi-model

ensemble (e.g. NAEFS project)– Bias correction– 2nd moment correction– CPC “consolidation” to quantify “value-added”

• Advanced dissemination strategies– E.g. NOMADS (“Fat server/Thin Client” technology)

• Next-Generation Air Traffic-control System (NGATS)– Geographically consistent solutions– Global to terminal scales– At least hourly updating globally

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Preparing for the Future (3)• Three principals for moving forward

1. Maturing, ensemble-based, probabilistic systems offer the most potential benefits across wide spectrum of forecast services

“Model of the day” is not a scientifically supportable

solution for the future2. Ensemble composition

a. Managed component diversityb. Components must be institutionally supported (operational

or major research institution)3. Product delivery

a. Time is critical (perishable product)b. Information availability must be maximized

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Production Suite: Conceptual Prototype

Products

• Three levels of information– Routinely delivered

1. Pointwise, single-valued, downscaled Most Likely Forecast from all available guidance on NDGD grid

2. Description of forecast uncertainty through probability density function (pdf)

– “On-demand” (via publicly accessible server)3. Individual ensemble member forecasts available• Prototype: NOMADS

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Production Suite: Conceptual PrototypeApplication Areas

• Focus on high impact weather– Hurricane intensity (and track) and coastal impacts– Other “High impact” defined by

• Users• Type of event

– Goal: “warn on forecast” for highest resolution events (e.g. tornado)• Examples of other new applications

– Surface transportation (e.g. “winter weather”)– Environmental monitoring (AQ + Atmos. Constituents)– Ocean (HABs & ecosystems, fog & visibility, coastal inundation,

dynamic storm surge)– Hydrology (water quality, drought)

• Hourly updating– RTMA AOR (through Reanalysis/Reforecast)– Regional assimilation– Global assimilation+

+ if requirement and available computing and human resources

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Production Suite: Schematic Overview

Model Region 1

Model Region 2

Global/Regional Model DomainAnalysis

• Concurrent execution of global and regional applications– More efficient execution of rapid updating

• In-core updating for analysis increments • Regional (CONUS, Alaska, Hawaii, Caribbean & Puerto Rico) • Global (if requirements and resources)

– All ensemble members may exchange information during execution• ESMF-based Common Modeling Infrastructure

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Analysis--------------

OtherForecastSystems

Physics(1,2,3)

ESMF Utilities(clock, error handling, etc)

Post processor & Product GeneratorVerification

Resolution change

1-11-21-32-12-22-3

ESMF Superstructure(component definitions, “mpi” communications, etc)

Multi-component ensemble+

Stochastic forcing

Coupler

Dynamics(1,2)

Application Driver

ESMF* Compliant Component System

* Earth System Modeling Framework (NCAR/CISL, NASA/GMAO, Navy (NRL), NCEP/EMC)

2, 3 etc: institutionally (non-NCEP) supported

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CFSMFS



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GENS/NAEFSGFS

Next Generation PrototypePhase 4 - 2015

Regional

Rap Refresh

GlobalHUR

SREF

Reforecast

Hydro / NIDIS/FF

Hydro

NAM

GDAS

RDAS

RTOFS RTOFSAQ


AQ

Computing factor: 81

Concurrent• GFS*• NAM• SREF Hourly• GDAS• RDAS• Rapid Refresh Expanded• Hurricane capability (hires)• Hydro/NIDIS• Reforecast

* Earlier delivery of GFS concurrent combined products from NAM, GFS, SREF

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CFS & MFS



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GENS/NAEFS

>100% of 2015 computing

Next Generation PrototypeFinal – 2017+


GLOBAL NGATS

HU

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Computing factor: > 240

ECOSYSTEMS

SPACE WEATHER

HENS

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Summary of Benefits• GDAS and RDAS with advanced assimilation techniques

– Use high density time and space observations more completely– Prepare for NPOESS, METOP, next-generation radar obs– Provide potential for expanded Rapid Refresh capability to serve

NGATS• Concurrency and unified post-processing provide

– Earlier delivery of GFS products– Real time boundary conditions for regional systems– Global and regional ensembles giving complementary uncertainty

measures based on different physical mechanisms– Unified “D(prog)/Dt view from all guidance products

• Reanalysis/Reforecast capability– Enables maximum forecast skill and independent skill assessment– Provides

• Operationally supported probabilistic systems• Updated skill evaluation as forecast systems evolve

• Grouping of regional ocean applications allows– Hurricanes to use real-time ocean state– Coastal applications to run concurrently

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Summary• Phased evolution of the NCEP Production Suite

– 2009-2015• Results in

– Improved services for high impact weather– Application of advanced data assimilation techniques for improved model

initial conditions– More efficient

• Use of computing• Incorporation of new product lines for improved services

– Earlier product delivery– More uniform and informative product stream

• Advanced ensemble suite including components supported outside NCEP• Improved statistical post-processing• Reforecast and Reanalysis become operationally supported

• Consistent with existing ESMF & global data assimilation development and interagency collaborations with– NASA– DOD– NCAR

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ThanksQuestions?

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Extras

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RTOFS

SREF NAM

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GFSHUR

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Current (2007)

GENS/NAEFS

Current - 2007


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CFSMFS



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GENS/NAEFSGFS


Regional

Rap Refresh

GlobalHUR

SREF

Reforecast

Hydro / NIDIS/FF

Hydro

NAM

GDAS

RDAS

RTOFS RTOFSAQ


AQ

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Community-based Development• Strategy and roles:

– Focus on single component instead of entire model system

– Collaborative, not competitive– NCEP/EMC

• Maintains primary components for each part of Production Suite and for each application

• Supports ESMF applications in operations• In collaboration with community

– Integrates new ESMF-based components into operations– Performs final testing and preparation of upgrades of supported

components in operations– Collaborators

• Provide – Component upgrades to be tested in operational setting– Institutional support for their contributed components– Diversity and expertise complementary to operations

• Work through DTC, JCSDA, CTB, etc.

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Conceptual Prototype:Numerical Forecast Guidance (1)

• Information should be optimally combined from all available sources– Domestic and international

models (global, e.g. NAEFS and regional)

– Same product format for all time scales (unified post-processing)

• Progress in numerical forecast system development should not be constrained by post-processing– Improved products come from

development of improved systems

Impact of Models on Day 1 Precipitation Scores

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• Robust training and outreach program must– Accompany new probabilistic-

based system– Support NWS Field Operations,

commercial sector and international users

– Support advanced dissemination of forecast information on all time and space scales

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Conceptual Prototype:Forecast System Development Areas

• Observations processing – JCSDA– Increased focus on quality control– Contribute to future observing system design

• Data assimilation– Coordinated development of advanced techniques

• Simplified 4-D Var (NCEP/EMC), annual updates thru 2008• “Classical” 4-D Var (with NASA/GMAO)• Ensemble Data Assimilation (with ESRL, UMD and others)• Development coordinated with NASA-NOAA-DOD JCSDA• 2008 decision 2010 implementation

– Better use of high time and space density, remotely-sensed data• Model accuracy (dynamics and physics)

– Hybrid vertical coordinate (sigma-pressure-theta)– Semi-lagrangian, Semi or Fully Implicit– Advanced radiation, shallow convection, deep convection– Stochastic forcing– Land surface tiling– Increased collaboration with community (Test Beds)

• Post-processing – Unified system across time and space scales and models– Includes bias correction and downscaling

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NCEP’s Next Generation Operational Forecast System

YearsYearsWeeksWeeksMinutesMinutes DaysDaysHoursHours SeasonsSeasonsMonthsMonths

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of G

uida

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Warnings & Alert Warnings & Alert CoordinationCoordination

WatchesWatches

ForecastsForecasts

Threat Assessments

GuidanceGuidance

OutlookOutlook

Lead Time

Protection of Protection of Life/PropertyLife/Property

Flood mitigationFlood mitigationNavigationNavigation

TransportationTransportationFire weatherFire weather

HydropowerHydropowerAgricultureAgriculture

EcosystemEcosystemHealthHealth

CommerceCommerceEnergyEnergy

Initi

al C

ondi

tion

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itivi

ty

Boundary Condition

SensitivityReservoir controlReservoir control

RecreationRecreation

Forecast Uncertainty

“Forecast Countdown for the Seamless Suite”

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Concurrent execution of global and regional forecast models (2)

Model Region 1

Model Region 2

Global/Regional Model DomainAnalysis

Local Solution

• Real time boundary and initial conditions available hourly

– “On-demand” downscaling to local applications• Similar to current hurricane runs but run either

– Centrally at NCEP OR– Locally (B.C, I. C. retrieved from on-line data at NCEP)

• No boundary or initial conditions older than 1 hour – Flexibility for “over capacity” runs

• Using climate fraction must be planned• No impact on remainder of services

• Consistent solution from global to local with a single forecast system and ensembles providing estimate of uncertainty

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ESMF Component Framework

Application

ChangeResolution

SurfaceCycling Atmosphere Post some other

Couplersome other Component

ATMDynamics

ATMPhysics Vertical Post Product

GeneratorOutput

GRIB/BUFR

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Wk2 MFS & CFS

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3-hourly GDAS (2)1-hourly RDAS (6)

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Added• 1-Hourly RDAS• 3-Hourly GDAS• Reanalysis/ Reforecast

Computing factor: 3

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Added• Hydro/NIDIS products Moved• GFS ½ h earlier Expanded• Hurricane & wave products Incorporated• Multi-domain rapid updating

Computing factor: 9

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Added• Flash flood products Moved• SREF concurrent to NAM Expanded• Reforecast capability

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EVOLUTION of the Next-Generation NCEP Production Suite (1)

Phase Date ComputerPower*

Human Resources

Implementation of new services

1 2009 3 +8(2 - 2008 3- 20072 – 20081 - 2009)

Increased forecast accuracy with hourly RDAS/LDAS, 3 hourly GDAS/GLDAS (2), and Advanced Data

Assimilation (2010)Reanalysis-Reforecast (5)

HABs (1)

2 2011 9 +6(2 – 20071 – 20083 – 2009)

ESMF-based in-core system (5)Downscaled 4 Domain RR with Firewx

Global hourly Aviation productsLand-HYDRO-NIDIS seasonal products (1)

3 2013 27 +3(1- 20102 – 2011)

Concurrent NAM, SREFCoupled Land-Hydro & Flash Flood (FF) guidance (1)

Biogeochemical tracers (2)

* Relative to NCEP’s 2007 computer

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EVOLUTION of the Next-Generation NCEP Production Suite (2)

Phase Date ComputerPower*

Human Resources

Implementation of new services

4 2015 81@ +5(2 – 2011)(3-2010)

Hourly GDAS+ Concurrent GFS+

Fully coupled global atmosphere-oceanAdvanced global ensemble system

Hurricane ensemble (1)@

Dynamic storm surge ensemble (1)@

NGATS support@

Final 2017(+)

240 +2(2 – 2015)

Concurrent GEFS/NAEFSHurricane ensemble

Dynamic storm surge ensembleFull ecosystem support (2)

NGATS support

* Relative to NCEP’s 2007 computer @ additional 3x computing upgrade in 2009required

+ If positive upgrade to services

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Fig. 2. Schematic diagram illustrating the one-way flow of initial value related information in a traditional NWP forecast process.

Traditional NWP Process

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Fig. 4. Schematic diagram illustrating the two-way flow of initial condition related information in the proposed new, integrated NWP forecast process.

Future NWP Process THORPEXPROGRAM

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Primary & Secondary Components and Models

• Primary components– Observations ingest, processing and quality control– Data assimilation– Forecast model– Post-processing– Product delivery

• Primary model– Used in data assimilation cycle– Supported by EMC for NCEP’s operations

• Risk reduction• Optimum maintenance• Optimum enhancement

– Continued exposure to observations– Model improvements impact analysis and forecast

• Secondary model– Initialized from analysis– Not cycled– Must add value to operational system

• Skill• Diversity• Unique application

– Supported institutionally by external (to EMC) organization• E.g. Navy (through NUOPC)• First line of support at EMC (one person)

– Applications• Ensemble membership (managed diversity)• Not fully supportable by EMC (e.g. ecosystems)

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The Environmental Forecast Process

Observations

Analysis

Model Forecast

Post-processed Model Data

Forecaster

User (public, industry…)

NumericalForecastSystem

Data Assimilation

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EMP Model Strategy & ESMF• Concept of operations

– Single system for global and regional models– Performance permitting

• Migration to single model or• Multiple dynamics and physics options in single structure

– Single verification, observations data base obeying WMO standards

– Single analysis code– System perturbations from

• Model diversity• Stochastic physics (preferred)

• System supports both operational and research components– Dynamics– Physics

• Overall positive experience at Met Office• ECMWF maintains single model & data assimilation

system for global wx & short-term climate forecasting

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Forecast System Development Strategy

• As far as possible, based on quantitative assessment:– A single physics– Applied across multiple scales– E. g. global weather and climate

• Possible extension to mesoscale• Successful for hurricane (GFS physics, NAM microphysics) GFDL)

• Excellent characteristics from all applications tested on other scales and implemented when ready

• Single model (and DA) structure makes this feasible• Ensemble application

– Requires approximately equal skill and system diversity– Secondary models and diverse components create manageable

system if ESMF compatible and institutional support• Disciplined competition fosters the best system

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Overview of Future Jigsaw

• Enabled by ESMF• Hourly global data assimilation analyses• Hourly global rapid refresh

– Supports NGATS• Concurrent global and mesoscale and

mesoscale ensemble• Reforecast window• Target 2015+

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Timing Summary (2015)Current (%) Future (%) Current Start

TimeFuture Start

TimeCurrent

End TimeFuture End

Time

GDAS 5.4 12.0 6:00 1:30 6:30 1:40

RDAS 3.2 7.2 5:30 1:30 6:00 1:40

GFSanal 4.4 0.8 2:55 1:30 3:20 1:40

NAManal 1.9 0.8 1:23 1:30 1:32 1:40

Rapid Refresh 2.2 4.8 1:25 1:30 1:47 1:47

NAMfcst 9.6 4.0 1:33 1:40 3:00 3:00

GFSfcst 12.8 6.5 3:21 1:40 4:40 3:30

GENS/NAEFS 7.1 7.6 3:23 3:30 5:30 6:00

SREF 7.8 7.6 0:30 1:30 1:22 3:40

HUR 7.7 7.8 4:30 3:40 4:30 6:00

RTOFS 7.7 7.2 xxxxx xxxxx xxxxx xxxxx

WAV 2.4 3.1 4:32 3:40 4:53 6:00

AQFS 2.4 2.1 2:00 2:30 5:00 5:00

CFS/MFS 25.4 17.1 xxxxxx xxxxx xxxxx xxxxx

Hydro-NIDIS 0 1.25 xxxxx xxxxx xxxxx xxxxx

Reforecast 0 11.5 None None

Bold=EarlierRed=Later

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The ultimate target is a completed NOAA Framework of ESMF

Components within which NOAA scientists can work efficiently.

One solution is outlined in the next few slides.

A Project to Create the NOAA/NCEP Framework of

ESMF Components Mark Iredell

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Proposed NOAA ESMF-based System Components (1)

• Change Resolution– Imports ATM state on one grid– Exports ATM state on another grid, possibly changing

variables and units• Surface Cycling

– Imports ATM boundary– Exports ATM boundary updated

• Atmosphere– Imports ATM state– Exports ATM state later in time

• Post– Imports ATM state– Exports selected products

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• Dynamics– Imports ATM state– Exports ATM state later in time

• Physics– Imports ATM state– Exports ATM state adjusted


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• Vertical Post– Imports ATM state– Exports fields on selected levels but model grid

• Product generator– Imports fields on one grid– Exports fields on another grid as requested

• Output– Imports fields– Writes GRIB2 files (or BUFR or netCDF)


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• Independent validation for each component that anyone can theoretically run

• Examples– Dynamical core

• Held-Suarez, etc.– Physics

• Single column, etc.– Atmosphere

• NWP and climate verifications and diagnostics– GFS with GDAS

• Full parallel validation


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Other Components

Other components that could be coupled to the global atmospheric model using ESMF:

• Obs. Processing• Variational Analysis• Ensemble Members• Mesoscale Model• Storm Model

• Ocean Model• Ice Model• Hydrology Model• Chemistry Model• Space Model

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Model FrameworkTime and People costs

• Estimated cost to NOAA for building:– 4 years– 17 man-years

• Maintenance cost unknown– Multiple major developers– Possible lack of coordination– Coordination may slow development and

system enhancement

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Code/Algorithm Assessment and/or Development

Transition Steps (Modeling)Identification for Selection1

2

Interface with Operational Codes3

Level I: Preliminary Testing (Lower Resolution)4

Level II: Preliminary Testing (DA/Higher Resolution)5

EMC Pre-Implementation Testing (Packaging/Calibration)6

NCO Pre-Implementation Testing7

Implementation/Delivery8

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EMCNCO

R&D Operations Delivery

Criteria

Transition from Research to Operations

Requirements

EMC

NCEP’s Role in the Model Transition Process

OPS Life cycleSupport

Service Centers

NOAAResearch

Concept of Operations

ServiceCenters

Test BedsJCSDA

CTBDTCJHT

User

Obs

erva

tion

Sy

stem

Launch List – Model Implementation Process

FieldOffices

Effort

EMC and NCO have critical roles in the transition from NOAA R&D to operationsOther Agencies

&International

Forecast benefits, Efficiency, IT Compatibility, Sustainability

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Component Requirements• Code standards and documentation

– ESMF interfaces fully described– Lightweight so as to not impede research

• Some compile-time and run-time flexibility– Somewhat flexible processor and thread layout– Somewhat flexible memory indexing layout– Somewhat flexible import and export fields

• Standard metadata– CF convention– GRIB2, etc.

• Distributed grid support under ESMF to enable coupling• Standalone validation

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Given this solution is acceptable, how can we manage to get there?

One framework project plan is given in the next few slides.

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Steps in creating model frameworka) Planning and coordinationb) GFS I/O componentsc) GFS ATM gridded componentd) GFS physics componente) GFS dynamics componentf) UMO dynamics componentg) GFS post componenth) Change resolution componenti) Surface cycling componentj) Coupler componentsk) Land componentl) Ocean componentm) Ice componentn) Aerosol componento) Ionosphere componentp) Mesoscale componentsq) GSI componentr) Configuration management

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Substeps in model framework (1)a) Planning and coordination (1.2)

1. Unified Model Infrastructure Group (UMIG)2. coordinate with EMC and other NOAA groups

b) GFS I/O components (0.2)1. I: input analysis, export distributed grid2. O: import distributed grid, export history file3. ESMF-ize

c) GFS ATM gridded component (0.2)1. import and export distributed reduced Gaussian grid2. internal state is both spectral and grid3. faster than current GFS4. keep dynamics and physics embedded at first5. ESMF-ize

d) GFS physics component (0.2)1. combine radiation and other physics2. standardize import and export states3. run on any set of points4. run with or without land model5. ESMF-ize

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Substeps in model framework (2)e) GFS dynamics component (0.2)

1. import and export distributed reduced Gaussian grid2. all spectral data and transforms are internal3. may have two phases (two modes of invocation)4. ESMF-ize

f) UMO dynamics component (0.2)1. Import and export distributed UMO grid2. may have two phases3. ESMF-ize

g) GFS post component (1.0)1. adapt WRF post to GFS2. import distributed model grid3. write data in GRIB24. ESMF-ize

h) Change resolution coupler component (0.2)1. import one ATM model state and convert to another2. ESMF-ize

i) Surface cycling component (0.2)1. adapt current surface cycling component2. ESMF-ize

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Substeps in model framework (3)j) Coupler components (4.0)

1. between ATM and ice and ocean for CFS2. adapted from Sheinin’s coupler3. ensemble coupler4. other couplers as well – generic coupler?5. ESMF-ize

k) Land component (1.0)1. ESMF-ize Noah land model

l) Ocean component (1.0)1. ESMF-ize MOM4 minimally2. EMSF-ize HYCOM

m) Ice component (1.0)1. ESMF-ize NCEP fast ice physics2. ESMF-ize GFDL slow ice physics

n) Aerosol component (1.0)1. ESMF-ize GOCART aerosol model

o) Ionosphere component (0.8)1. ESMF-ize IDEA ionosphere model

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Substeps in model framework (4)p) Mesoscale components (2.6)

1. non-WRF NMM2. WRF and HWRF3. run nested or standalone4. ESMF-ize

q) GSI component (1.6)1. minimal subroutinization2. ESMF-ize

r) Configuration management (0.4)1. Install and maintain Subversion2. Subversion training and support3. Version control on scripts and code for CCS, R&D, and local servers

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Dependence on ESMF software developed and maintained by NCAR

• Risk: e.g., ESMF did not compile on “mist” (turned out to be a compiler deficiency)

• Potential critical mass of users(NOAA, DOD, NASA)

• Potential support from IT contractors• Further layering (e.g., MAPL from NASA)

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What is an ESMF Component?

• An ESMF Component has 3 methods: initialize, run, finalize

• Methods have a standard interface, including 1 import state and 1 export state

• A component also has an internal state, which contains whatever persistent data the component needs, and which is generally not visible to other components

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anom

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corr

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* 10

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2 5 8 11starting month

Consolidation Ensemble AverageBest single model

Potential Benefits of Using 9 ModelsLead 5 Nino34 forecast 1981-2001

Gaussian Kernels

“Frequentist” methods

“Bayesian” methods

Construction of Optimum Forecast Guidance from Multi-Model Ensembles

1. Multiple independent realizations2. Historical “reforecast” data set3. Optimal postprocessing to produce “the best” forecast4. Compact information dissemination

Documents

1 The Proposed Next-Generation NCEP Production Suite EMC Senior Staff January 2007 NCEP Production Suite Weather, Ocean, Land & Climate Forecast Systems