It Began with a Vision: L.F. Richardson’s “Forecast Factory”

From Megaflops & ModemsFrom Megaflops & Modemstoto

Teraflops & Lightwaves:Teraflops & Lightwaves:A Brief History of Convective Storm A Brief History of Convective Storm

Simulation and Prospects for Operational Simulation and Prospects for Operational Numerical PredictionNumerical Prediction

Kelvin K. DroegemeierKelvin K. DroegemeierSchool of Meteorology and School of Meteorology and

Center for Analysis and Prediction of StormsCenter for Analysis and Prediction of StormsUniversity of OklahomaUniversity of Oklahoma

School of Meteorology 40School of Meteorology 40thth Anniversary AnniversaryScientific SympoisumScientific Sympoisum

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It Began with a Vision: L.F. It Began with a Vision: L.F. Richardson’s “Forecast Factory”Richardson’s “Forecast Factory”

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It Began with a Computer: ENIACIt Began with a Computer: ENIAC

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It Began with a Computer: ENIACIt Began with a Computer: ENIAC

Not the first computer, but it opened the Not the first computer, but it opened the door for the “von Neumann door for the “von Neumann architecture”architecture”

Built to generate ballistics tablesBuilt to generate ballistics tables Weighed 30 tonsWeighed 30 tons Had 18,000 vacuum tubes, 1,500 relays Had 18,000 vacuum tubes, 1,500 relays

thousands of resistors, capacitors, thousands of resistors, capacitors, inductorsinductors

Peak speed of 5000 adds/second and Peak speed of 5000 adds/second and 300 multiplies/sec300 multiplies/sec

Played a key role in the development of Played a key role in the development of the hydrogen bombthe hydrogen bomb

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Some Interesting ComparisonsSome Interesting Comparisons

The ENIAC was 1000 times faster than The ENIAC was 1000 times faster than its predecessorits predecessor

A 600 MHz Pentium III processor is A 600 MHz Pentium III processor is 240,000 times faster than the ENIAC240,000 times faster than the ENIAC

A desktop PC with 128 mbytes of RAM A desktop PC with 128 mbytes of RAM can store 640,000 times as much data can store 640,000 times as much data as the ENIAC as the ENIAC

The ENIAC was decommissioned in 1955The ENIAC was decommissioned in 1955 The ENIAC ran the first NWP calculation The ENIAC ran the first NWP calculation

(Charney et al., 1950)(Charney et al., 1950)

Charney, Fjortoft, and von Charney, Fjortoft, and von Neumann (1950)Neumann (1950)

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Numerically Numerically integrated the integrated the barotropic vorticity barotropic vorticity equationequation

736 km resolution736 km resolution 24 hour forecast24 hour forecast Encountered Encountered

nonlinear instability nonlinear instability (later solved by Norm (later solved by Norm Phillips)Phillips)

Did exploratory work Did exploratory work on baroclinic on baroclinic equationsequations

The Computational GridThe Computational Grid

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ENIAC-On-A-ChipENIAC-On-A-Chip

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http://www.ee.upenn.edu/~jan/_vti_bin/shtml.dll/eniac_chip.html/map

Parallel, Parallel, ParallelParallel, Parallel, Parallel

Vector/Pipeline

Shared MemoryVector/Parallel

Distributed MemoryScalable Parallel

The Future: Inexpensive Clusters The Future: Inexpensive Clusters Built Around Commodity Processors Built Around Commodity Processors

and Linuxand Linux

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Pittsburgh Supercomputing Center’s Pittsburgh Supercomputing Center’s 5 Teraflop Cluster5 Teraflop Cluster

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Cloud-Scale ModelingCloud-Scale Modeling 1950’s: Early 1-D models (Malkus, Warner, 1950’s: Early 1-D models (Malkus, Warner,

Holton)Holton)– Lagrangian parcel representationsLagrangian parcel representations– Simple microphysics and entrainmentSimple microphysics and entrainment– Neglected vertical PGF (explicitly)Neglected vertical PGF (explicitly)– Very controversial results, but a good startVery controversial results, but a good start

1960’s: Early 2-D models (Ogura, Lilly)1960’s: Early 2-D models (Ogura, Lilly)– Axial or planar symmetryAxial or planar symmetry– Inverse cascades (couldn’t reproduce similarity Inverse cascades (couldn’t reproduce similarity

theory)theory)– Basic microphysicsBasic microphysics– Soong and Ogura (1973) was a watershed paperSoong and Ogura (1973) was a watershed paper

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Cloud-Scale ModelingCloud-Scale Modeling 1970’s: Emergence of 3-D Models1970’s: Emergence of 3-D Models

– Steiner was the first (1973)Steiner was the first (1973)– Computers were still not sufficiently powerfulComputers were still not sufficiently powerful– Successes by Lipps, Cotton, othersSuccesses by Lipps, Cotton, others– Arrival of Cray-1 at NCAR and the Arrival of Cray-1 at NCAR and the

collaboration of Joe Klemp and Bob collaboration of Joe Klemp and Bob Wilhelmson marked the turning pointWilhelmson marked the turning point

Early Contour Plot of Early Contour Plot of Horizontal Wind from 3-D Horizontal Wind from 3-D

SimulationSimulation

Courtesy R. Wilhelmson, University of Illinois

Early “Animation” of a 3-D Early “Animation” of a 3-D SimulationSimulation


3-D Structure Based on 3-D Structure Based on TrajectoriesTrajectories


Pipe Cleaner Perspective!Pipe Cleaner Perspective!


Computer-Generated Pipe Computer-Generated Pipe Cleaners!Cleaners!


From Simulation to PredictionFrom Simulation to Prediction


Observations

From Simulation to PredictionFrom Simulation to Prediction


Observations Simulation

Based on Simulations, Based on Simulations, Observations (radar, chase Observations (radar, chase teams), and Theory, We’ve teams), and Theory, We’ve

LearnedLearned

Why storms splitWhy storms split Why storms have deviate motionWhy storms have deviate motion How storms acquire rotationHow storms acquire rotation How to determine storm timeHow to determine storm time Something about storm energeticsSomething about storm energetics

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Translating this Knowledge to Translating this Knowledge to Operations: Current Operational Operations: Current Operational

GridGrid

What Do Current Operational What Do Current Operational Forecast Models Predict?Forecast Models Predict?

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What Causes Most of the What Causes Most of the Problems?Problems?

Intense severeIntense severespring and winter spring and winter storms that create storms that create high-impact, locally high-impact, locally disruptive weatherdisruptive weather

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An Emerging Question in the Late An Emerging Question in the Late 1980s1980s

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Can computer forecastCan computer forecastmodel technology. . .model technology. . .

. . . explicitly predict this. . . explicitly predict thistype of weather?type of weather?

In 1988 … Supercomputers and In 1988 … Supercomputers and Networking Were ExplodingNetworking Were Exploding

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In 1988 … NEXRAD Was Becoming a In 1988 … NEXRAD Was Becoming a RealityReality

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But … Most Areas Would Have Only But … Most Areas Would Have Only Single-Doppler CoverageSingle-Doppler Coverage

real real windwind

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observedobservedcomponentcomponent

This Led Doug Lilly and His StudentsThis Led Doug Lilly and His Studentsto Explore Single-Doppler Velocity to Explore Single-Doppler Velocity

Retrieval (SDVR)Retrieval (SDVR)

Center for Analysis and Center for Analysis and Prediction of Storms Prediction of Storms

(CAPS)(CAPS) One of first 11 NSF Science and One of first 11 NSF Science and

Technology Centers established in 1989Technology Centers established in 1989 Mission of CAPS: To Mission of CAPS: To

– demonstrate the practicability of numerically demonstrate the practicability of numerically predicting local, high-impact storm-scale predicting local, high-impact storm-scale spring and winter weather, and spring and winter weather, and

– to develop, test, and help implement a to develop, test, and help implement a complete analysis and forecast systemcomplete analysis and forecast system appropriate for appropriate for operational, commercial, and operational, commercial, and researchresearch applications applications

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The Key Scientific The Key Scientific QuestionsQuestions

Can the 3-D wind and mass fields be Can the 3-D wind and mass fields be retrievedretrieved reliably from single Doppler radar observations and reliably from single Doppler radar observations and used to used to initializeinitialize a prediction model? a prediction model?

Which storm-scale structures and processes are Which storm-scale structures and processes are most most predictablepredictable, and will fine-scale details , and will fine-scale details enhance or reduce predictability?enhance or reduce predictability?

What What physicsphysics is required, and do we understand it is required, and do we understand it well enough for practical application?well enough for practical application?

What What observationsobservations are most critical? are most critical? What networking & computational What networking & computational infrastructuresinfrastructures

and coding techniques are needed to support and coding techniques are needed to support high-resolution NWP?high-resolution NWP?

How can useful decision making How can useful decision making informationinformation be be generated from forecast model output?generated from forecast model output?

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Sample SDVR ResultSample SDVR Result

Dual-DopplerDual-Doppler SDVR-RetrievedSDVR-Retrieved

Weygandt (1998)Weygandt (1998)

5 April 1999 - Impact of NEXRAD 5 April 1999 - Impact of NEXRAD DataData

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15 Z Reflectivity

3 hr ARPS CREF Forecast (9 km) WITH RADAR

DATA and SDVRValid 15Z

3 hr ARPS Reflectivity Forecast (9 km) – NO

RADAR DATAValid 15Z

Courtesy S. Weygandt and J. Levit

The Impact of Horizontal ResolutionThe Impact of Horizontal Resolution

CAPS 12-hourForecast

Radar

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Radar(Tornadoes

in Arkansas)

Radar(Tornadoes

in Arkansas)

CAPS 6-hour Regional Forecast

Radar

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Radar CAPS 6-hour LocalForecast

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Detail is a Double-Edged Detail is a Double-Edged Sword!Sword!

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Actual Event

30 miles

D/FW Airport

A perfectly predicted storm having a position error A perfectly predicted storm having a position error of 30 miles may be a terrible forecast on the scale of 30 miles may be a terrible forecast on the scale

of a single airportof a single airport

Forecast

Where Do We Go From Where Do We Go From Here?Here?

CAPS has provided some evidence of CAPS has provided some evidence of small-scale predictability, but …small-scale predictability, but …

Operational prediction of storm-scale Operational prediction of storm-scale weather will requireweather will require– better understanding of predictability (?)better understanding of predictability (?)– better understanding of scale interactionbetter understanding of scale interaction– intense training by forecasters and intense training by forecasters and

fundamental changes in their fundamental changes in their interpretation/use of model outputinterpretation/use of model output

– more computing powermore computing power– access to NEXRAD radar data and better access to NEXRAD radar data and better

techniques for retrieval and assimilationtechniques for retrieval and assimilations fn

Current Status of the CRAFT Real Time Current Status of the CRAFT Real Time NEXRAD Level II Ingest Test BedNEXRAD Level II Ingest Test Bed

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Links to be Established by This Time Next Links to be Established by This Time Next YearYear

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The Future of Operational NWPThe Future of Operational NWP

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10 km

3 km

1 km

20 km CONUS Ensembles

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10 km

3 km

3 km

3 km3 km

10 km

20 km CONUS Ensembles

The Future of Operational The Future of Operational NWPNWP

The Future of Operational NWP??The Future of Operational NWP??Virtual Machine RoomVirtual Machine Room

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The Private Sector Enters The Private Sector Enters the NWP Gamethe NWP Game

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My “Prediction” of the My “Prediction” of the FutureFuture

NCEP begins operating the WRF model (or NCEP begins operating the WRF model (or variants thereof)variants thereof)– at 10 km resolution: 2003-2004at 10 km resolution: 2003-2004– at 3 km resolution (nested) using NEXRAD at 3 km resolution (nested) using NEXRAD

radar data: 2006radar data: 2006– at 1 km resolution (nested): 2008at 1 km resolution (nested): 2008– at 1 km resolution North America: 2010-2012at 1 km resolution North America: 2010-2012

By 2005, the private sector weather By 2005, the private sector weather industry will achieve $100B in revenuesindustry will achieve $100B in revenues

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It Began with a Vision: L.F. Richardson’s “Forecast Factory”

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