From Megaflops & Modems to Teraflops & Lightwaves: A Brief History of Convective Storm Simulation and Prospects for Operational Numerical Prediction Kelvin K. Droegemeier School of Meteorology and Center for Analysis and Prediction of Storms University of Oklahoma School of Meteorology 40 th Anniversary Scientific Sympoisum

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

It Began with a Computer: ENIAC

n Not the first computer, but it opened the door for the “von Neumann architecture” n Built to generate ballistics tables n Weighed 30 tons n Had 18,000 vacuum tubes, 1,500 relays thousands of resistors, capacitors, inductors n Peak speed of 5000 adds/second and 300 multiplies/sec n Played a key role in the development of the hydrogen bomb

Some Interesting Comparisons n The ENIAC was 1000 times faster than its predecessor n A 600 MHz Pentium III processor is 240,000 times faster than the ENIAC n A desktop PC with 128 mbytes of RAM can store 640,000 times as much data as the ENIAC n The ENIAC was decommissioned in 1955 n The ENIAC ran the first NWP calculation (Charney et al., 1950)

Charney, Fjortoft, and von Neumann (1950) n Numerically integrated the barotropic vorticity equation n 736 km resolution n 24 hour forecast n Encountered nonlinear instability (later solved by Norm Phillips) n Did exploratory work on baroclinic equations

The Computational Grid

ENIAC-On-A-Chip

Parallel, Parallel, Parallel Vector/Pipeline Shared Memory Vector/Parallel Distributed Memory Scalable Parallel

The Future: Inexpensive Clusters Built Around Commodity Processors and Linux

Pittsburgh Supercomputing Center’s 5 Teraflop Cluster

Cloud-Scale Modeling n 1950’s: Early 1-D models (Malkus, Warner, Holton) –Lagrangian parcel representations –Simple microphysics and entrainment –Neglected vertical PGF (explicitly) –Very controversial results, but a good start n 1960’s: Early 2-D models (Ogura, Lilly) –Axial or planar symmetry –Inverse cascades (couldn’t reproduce similarity theory) –Basic microphysics –Soong and Ogura (1973) was a watershed paper

Cloud-Scale Modeling n 1970’s: Emergence of 3-D Models –Steiner was the first (1973) –Computers were still not sufficiently powerful –Successes by Lipps, Cotton, others –Arrival of Cray-1 at NCAR and the collaboration of Joe Klemp and Bob Wilhelmson marked the turning point

Early Contour Plot of Horizontal Wind from 3-D Simulation Courtesy R. Wilhelmson, University of Illinois

Early “Animation” of a 3-D Simulation Courtesy R. Wilhelmson, University of Illinois

3-D Structure Based on Trajectories Courtesy R. Wilhelmson, University of Illinois

Pipe Cleaner Perspective! Courtesy R. Wilhelmson, University of Illinois

Computer-Generated Pipe Cleaners! Courtesy R. Wilhelmson, University of Illinois

From Simulation to Prediction Courtesy R. Wilhelmson, University of Illinois Observations

From Simulation to Prediction Courtesy R. Wilhelmson, University of Illinois Observations Simulation

Based on Simulations, Observations (radar, chase teams), and Theory, We’ve Learned n Why storms split n Why storms have deviate motion n How storms acquire rotation n How to determine storm time n Something about storm energetics

Translating this Knowledge to Operations: Current Operational Grid

What Do Current Operational Forecast Models Predict?

What Causes Most of the Problems? n Intense severe spring and winter storms that create high-impact, locally disruptive weather

An Emerging Question in the Late 1980s Can computer forecast model technology explicitly predict this type of weather?

In 1988 … Supercomputers and Networking Were Exploding

In 1988 … NEXRAD Was Becoming a Reality

But … Most Areas Would Have Only Single-Doppler Coverage

realwind observedcomponent This Led Doug Lilly and His Students to Explore Single-Doppler Velocity Retrieval (SDVR)

Center for Analysis and Prediction of Storms (CAPS) n One of first 11 NSF Science and Technology Centers established in 1989 n Mission of CAPS: To –demonstrate the practicability of numerically predicting local, high-impact storm-scale spring and winter weather, and –to develop, test, and help implement a complete analysis and forecast system appropriate for operational, commercial, and research applications

The Key Scientific Questions n Can the 3-D wind and mass fields be retrieved reliably from single Doppler radar observations and used to initialize a prediction model? n Which storm-scale structures and processes are most predictable, and will fine-scale details enhance or reduce predictability? n What physics is required, and do we understand it well enough for practical application? n What observations are most critical? n What networking & computational infrastructures and coding techniques are needed to support high-resolution NWP? n How can useful decision making information be generated from forecast model output?

Uniqueness of CAPS n Looking at the entire storm-scale prediction problem n Cohesive team of scientists with a single purpose and unified vision n Dealing with computational as well as meteorological aspects n Stable, long-term funding

The CAPS Advanced Regional Prediction System (ARPS)

Sample SDVR Result Dual-Doppler SDVR-Retrieved Weygandt (1998)

Sample SDVR Result Dual-Doppler SDVR-Retrieved Weygandt (1998)

5 April Impact of NEXRAD Data 15 Z Reflectivity 3 hr ARPS CREF Forecast (9 km) WITH RADAR DATA and SDVR Valid 15Z 3 hr ARPS Reflectivity Forecast (9 km) – NO RADAR DATA Valid 15Z Courtesy S. Weygandt and J. Levit

The Impact of Horizontal Resolution CAPS 12-hour Forecast Radar (Tornadoes in Arkansas)

Radar (Tornadoes in Arkansas) CAPS 6-hour Regional Forecast Radar The Impact of Horizontal Resolution

RadarCAPS 6-hour Local Forecast The Impact of Horizontal Resolution

Detail is a Double-Edged Sword! Actual Event 30 miles D/FW Airport A perfectly predicted storm having a position error of 30 miles may be a terrible forecast on the scale of a single airport Forecast

Where Do We Go From Here? n CAPS has provided some evidence of small- scale predictability, but … n Operational prediction of storm-scale weather will require –better understanding of predictability (?) –better understanding of scale interaction –intense training by forecasters and fundamental changes in their interpretation/use of model output –more computing power –access to NEXRAD radar data and better techniques for retrieval and assimilation

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

Links to be Established by This Time Next Year

The Future of Operational NWP 10 km 3 km 1 km 20 km CONUS Ensembles

10 km 3 km 10 km 20 km CONUS Ensembles The Future of Operational NWP

The Future of Operational NWP?? Virtual Machine Room

The Private Sector Enters the NWP Game

My “Prediction” of the Future n NCEP begins operating the WRF model (or variants thereof) –at 10 km resolution: –at 3 km resolution (nested) using NEXRAD radar data: 2006 –at 1 km resolution (nested): 2008 –at 1 km resolution North America: n By 2005, the private sector weather industry will achieve $100B in revenues