# May, 2002Numerical Weather Prediction 1 Robert R. Gotwals, Jr. (Bob2) Computational Science Educator The Shodor Education Foundation, Inc.

## Presentation on theme: "May, 2002Numerical Weather Prediction 1 Robert R. Gotwals, Jr. (Bob2) Computational Science Educator The Shodor Education Foundation, Inc."— Presentation transcript:

May, 2002Numerical Weather Prediction 1 Robert R. Gotwals, Jr. (Bob2) Computational Science Educator The Shodor Education Foundation, Inc. http://www.shodor.org http://www.shodor.org/talks/nwp

May, 2002Numerical Weather Prediction 2 Session Goals Describe application, algorithm, and architecture Describe and demonstrate the various NWP programs and codes Describe appropriate and authentic classroom activities using online NWP tools

May, 2002Numerical Weather Prediction 3 Application - First Principles Definition: The use of computer models to predict the future state of the atmosphere given observations and equations that describe relevant physical processes Some givens: Weather prediction is really hard Synoptic scale calculations, but local influences Equations are nonlinear

May, 2002Numerical Weather Prediction 4 Application - Results Example plots Temperature Dewpoint Mean sea level pressures (MSLP) Winds, surface and aloft Cloud cover Precipitation and types Severe weather indices CAPE Helicity

May, 2002Numerical Weather Prediction 5 Algorithm - NWP Desks Desk seat 1: calculates east-west component of the wind Desk seat 2: calculates north-south component of the wind Desk seat 3: keeps track of the air entering or leaving the box. If more is coming in than going out, decides how much air rises or sinks Desk seat 4: calculates the effects of adding or taking away heat Desk seat 5: keeps track of water in all forms and how much is changing to or from vapor, liquid, or ice Desk seat 6: calculates the air temperature, pressure, and density

May, 2002Numerical Weather Prediction 6 Architecture - Platforms NWP requires significant computing power True supercomputing required –Gigaflops - billions of calculations (floating point operations) per second –Teraflop - trillions of calculations per second Data storage –NCAR - late 2000, 200 terabytes of data stored NCAR machine –11th most powerful supercomputing in the world –IBM SP Power 3 –1260 CPUs (processors) –Peak capabilities: 1890 Gigaflops

May, 2002Numerical Weather Prediction 7 Architecture - Codes General categories –By resolution –By scale Global (northern hemisphere) National relocatable –By outlook (time-based) Well-known codes –Nested Grid Model (NGM) –ETA –Aviation Model (AVN) –Rapid Update Cycle (RUC) –Medium Range Forecast (MRF) –Mesoscale Model 5 (MM5)

May, 2002Numerical Weather Prediction 8 Nested Grid Model (NGM) National model Short-range model (+48 hours), every 6 hour forecasts Forecast output –Temperature –Precipitation –Upper and lower trough positioning –Surface highs and lows Grid size: 80 km Operational status: being phased out http://weather.uwyo.edu/models/fcst/index.html?MODEL=ngm

May, 2002Numerical Weather Prediction 9 ETA Name comes from eta coordinate system Short-range model Four runs daily: 0000Z, 0600Z, 1200Z, 1800Z 32 km horizontal domain, with 45 vertical layers Significantly outperforms other models in precipitation predictions http://weather.uwyo.edu/models/fcst/index.html?MODEL=eta

May, 2002Numerical Weather Prediction 10 Rapid Update Cycle Regional model Short-term forecasts –Up to 12 hours Focuses on mesoscale weather features 25 vertical layers, 40 km horizontal resolution New experimental version: MAPS RUC/MAPS generate significant amount of data http://weather.unisys.com/ruc/index.html

May, 2002Numerical Weather Prediction 11 Medium Range Forecast (MRF) Model Global model Medium to long-range predictions: 60 to 240 hours Resolution: 150 km Other global models –UKMET –ECMWF –Global Ocean Model

May, 2002Numerical Weather Prediction 12 Aviation Model Generates aviation- focused data 42 vertical layers, 100 km horizontal resolution Advantage: medium- range forecasting (up to 72 hours) One of the oldest operational models Data results available mostly in MOS (model output statistics) format http://weather.unisys.com/aviation/index.html

May, 2002Numerical Weather Prediction 13 MM5 Fifth generation mesoscale NWP Study types –hurricanes –cyclones –monsoons –fronts (formation, interactions) –land-sea breeze meteorology –urban heat islands –mountain-valley circulations http://rain.mmm.ucar.edu/mm5/

May, 2002Numerical Weather Prediction 14 Sample Prediction Question: assuming precipitation, what will it be? Tools: –Atmospheric sounding (weather balloon data)Atmospheric sounding Shows temperature and dewpoint temperature from surface to upper atmosphere –Flowchart: precipitation type decision tree Analysis/solution shown on next slide

May, 2002Numerical Weather Prediction 15 Sample Prediction - Solution

May, 2002Numerical Weather Prediction 16 Classroom Integration - Forecasting Rules of thumb Will it be cloudy or clear? –On the 700-mb forecast chart, the 70% relative humidity line usual encloses areas that are likely to have clouds Will it rain? –On the 700-mb forecast chart, the 90% relative humidities line often encloses areas where precipitation is likely. Will it rain or snow? –On the 850-mb forecast chart, snow is likely north of the -5 C (23 F) isotherm, rain to the sou th

May, 2002Numerical Weather Prediction 17 Classroom Integration - Weather observations Correlating low-tech weather observations –Use instant weather prediction chart –Shows various weather 24 hours out based on easily observable meteorological phenomenon –Can correlate this with model data http://www.shodor.org/bob2/wx/weather predict.html

May, 2002Numerical Weather Prediction 18 Classroom Integration Good starting place: meteograms –Relatively easy to interpret –Contain a lot of data –Typically project out 24 to 72 hours –Relatively good resolution (normally 22 km) –Available from a variety of models http://www.emc.ncep.noaa.gov/mmb/meteograms/

May, 2002Numerical Weather Prediction 19 Classroom Integration Harder: atmospheric soundings graphs Substantial amounts of information Graphical and text-based information –Graphical: temperature, dewpoint temperatures, wind speeds and directions –Text: key meteorological indices

May, 2002Numerical Weather Prediction 20 Questions? Chat Sessions –Monday, May 13 3:30- 4:30 PM and 6:00-7:00 PM –Wednesday, May 15 3:30- 4:30 PM –Monday, May 20 6:00- 7:00 PM –Thursday, May 23 3:30- 4:30 PM and 6:00-7:00 PM

Download ppt "May, 2002Numerical Weather Prediction 1 Robert R. Gotwals, Jr. (Bob2) Computational Science Educator The Shodor Education Foundation, Inc."

Similar presentations