1 group 1: modeling and data assimilation summary: 1. hpc access, hpc access, hpc access 2....

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Group 1: Modeling and Data Assimilation

Summary:1. HPC access, HPC access, HPC access2. resources: personnel inside (e.g. EMC) and externally funded

(NOAA, other projects, visitors), code documentation/wikis, computing (e.g. CFSv3 50PB!)

3. "Easy" access to model codes and development tools, e.g. a "hierarchy" of model components, metrics

4. communication --on above with EMC points of contact5. Efficient R2O process involves above6. sustained investment (by EMC, NCEP, NWS, NOAA...)

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Facilitating external collaboration in CFS development

• The primary task of CFS is operational coupled ensemble prediction between 2 weeks and a year.

• Our vision is that all NCEP prediction models be the most skillful in the world, and their outputs be freely, widely and wisely used.

• The US has the largest and strongest scientific community in weather and climate science in the world.

• This community would embrace a CFS designed to facilitate community use, testing and collaborative model development, in which they have a stake. This process has begun but to transform CFS it must go much further.

• Keeping the CFS tightly unified with GFS will leverage the resources of the US weather community and allow the software engineering and infrastructure needed for this vision.

Chris Bretherton, UW

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Examples of external CFS users

• Use CFS outputs and reanalyses (already active) for diverse applications (hydro, fire, ag, health, etc.)

• Use CFS as part of an MME (already active)• Run CFS for fundamental analysis of climate variability or

extreme events• Run CFS for predictability and attribution studies• Improve data assimilation methodology / OSSEs• Improve model physics and dynamics; reduce biases• Add new earth system processes (e.g. chemistry)• Improve ensemble statistics …


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Moving to this vision• With enough R2O support, a large active pool of external model users

accelerates system improvement, as they are motivated to help solve the problems they encounter

• Required elements of such R2O support ✓ CPT-like support for transitioning promising high-priority

improvements to operations ✓ Clear metrics to measure model improvement ✓ Clear internal strategic plan for model development - Comprehensive on-line documentation - Extensive, user-friendly run scripts, input files, and basic diagnostic

packages on accessible HPC. - Clear internal EMC points of contact• A sustained investment in these elements pays off!


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TOWARDS BUILDING A PROTOTYPE OF THE NEXT GENERATION

UNIFIED GLOBAL COUPLED ANALYSIS AND

FORECAST SYSTEM AT NCEP (UGCS)

Earth-Next

Dreamliner

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Atmosphere, Land, Ocean, Seaice, Wave, Chemistry, Ionosphere

Data Assimilation cycleAnalysis frequency HourlyForecast length 9 hoursResolution 10 kmEnsemble members 100Testing regime 3 years (last 3 years)Upgrade frequency 1 year

UNIFIED GLOBAL COUPLED SUITEDATA ASSIMILATION

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Weather ForecastsForecast length 10 daysResolution 10 kmEnsemble members 10/dayTesting regime 3 years (last 3 years)Upgrade frequency 1 year

UNIFIED GLOBAL COUPLED SUITEWEATHER FORECASTS

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Sub-seasonal forecastsForecast length 6 weeksResolution 30 kmEnsemble members 20/dayTesting regime 20+ years (1999-present)Upgrade frequency 2 year

UNIFIED GLOBAL COUPLED SUITESUB-SEASONAL FORECASTS

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Seasonal ForecastsForecast length 9 monthsResolution 50 kmEnsemble members 40 (lagged)Testing regime 40+ years (1979-present)Upgrade frequency 4 year

UNIFIED GLOBAL COUPLED SUITESEASONAL FORECASTS

Resources: Human (Building the Dream Team)Climate Team Lead: Suru Saha ( Care-Taker-Acting)

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Component Data Assimilation ModelAtmosphere Jack Woollen,

Malaquias PenaDaryl Kleist

Shrinivas MoorthiYu-Tai Hou

Land Jiarui DongJesse Meng

Helin WeiRongqian Yang

Ocean Dave Behringer (MOM)Steve Penny (MOM)

Xu Li (NSST)Avichal Mehra (HYCOM)

Jiande Wang (MOM)Zulema Garaffo (HYCOM)

Sea-Ice Xingren WuBob Grumbine

Waves Paula Etala Arun ChawlaHenrique Alves

Aerosols Sarah Lu

Code Manager NEMSInfrastructure Patrick Tripp Mark Iredell

Diagnostics/ Verification/single column model, physics component simulators

Suru Saha, NCEP/EMC

Resources: Compute/Storage

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• Development work on WCOSS, with collaborations on Theia, Gaea, etc.

• Model code/scripts on EMC/Svn.

• Production/reforecasts -- “Cloud Computing”? (has to be done on a computer we can manage ourselves with dedicated queues and computer hours –”dedicated resources”). TBD NLT Jan 2017.

• Storage/Dissemination: HPSS, the “Cloud”(?) –e.g. Amazon and/or Internal/NCO . TBD NLT Jan 2017.

• Resolution upgrade (4x) and number of ensemble members (5x) = 20x ~50PB!

Suru Saha, NCEP/EMC

Collaborations

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• Svn: codes, scripts to be checked out by collaborators, including single column model, physics component simulators.

• “Test Harness” 9 years/seasons of warm/cold/neutral ENSO (for fast turnaround to test e.g. physics changes):• May starts -summer (JJA)• Nov starts -winter (DJF)

• Control runs to be done at EMC, with initial & boundary conditions, etc available.

• Corresponding Diagnostics and Verification Packages, “Climate Scorecard”.

• Visiting Scientist Program to promote R2O, example to invite leading scientists to visit EMC for 1-12 months.

Suru Saha, NCEP/EMC

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Predictions for all spatial and temporal scales will be ensemble based.

There will be a continuous process of making coupled Reanalysis and Reforecasts for every implementation (weather, sub-seasonal and seasonal)

Since the resolution of all parts of the system is usually increased with every new implementation (in proportion to the increased computing power currently available), there is the possibility of exploring cheaper cloud computing and storage options for making these reanalysis/reforecasts.

UNIFIED GLOBAL COUPLED SUITENEW PARADIGM

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Coupled Model Ensemble Forecast

NEMS

OCE

ANSE

A-IC

EW

AVE

LAN

DAE

ROAT

MO

S

Ensemble Analysis (N Members)

OUTPUT

Coupled Ensemble Forecast (N members)

INPUT

Coupled Model Ensemble Forecast

NEMS

OCEAN

SEA-ICEW

AVELAN

DAERO

ATMO

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NCEP Coupled Hybrid Data Assimilation and Forecast System

1 group 1: modeling and data assimilation summary: 1. hpc access, hpc access, hpc access 2....

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