Transcript PowerPoint Presentation - Numerical Weather Prediction

Numerical Weather
Prediction
Robert R. Gotwals, Jr. (“Bob2”)
Computational Science Educator
The Shodor Education
Foundation, Inc.
http://www.shodor.org
http://www.shodor.org/talks/nwp
May, 2002
Numerical Weather
Prediction
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Session Goals
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Describe application,
algorithm, and
architecture
Describe and demonstrate
the various NWP
programs and codes
Describe appropriate and
authentic classroom
activities using online
NWP tools
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Prediction
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Application - First
Principles
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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:
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Weather prediction is
really hard
Synoptic scale
calculations, but local
influences
Equations are nonlinear
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Prediction
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Application - Results
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Example plots
• Temperature
• Dewpoint
• Mean sea level
pressures (MSLP)
• Winds, surface and aloft
• Cloud cover
• Precipitation and types
• Severe weather indices
• CAPE
• Helicity
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Algorithm - NWP
Desks
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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
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Architecture Platforms
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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
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Architecture - Codes
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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)
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Nested Grid Model
(NGM)
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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
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Prediction
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ETA
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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
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Prediction
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Rapid Update Cycle
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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
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Prediction
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Medium Range
Forecast (MRF) Model
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Global model
Medium to long-range
predictions: 60 to 240
hours
Resolution: 150 km
Other global models
– UKMET
– ECMWF
– Global Ocean Model
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Prediction
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Aviation Model
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Generates aviationfocused data
42 vertical layers, 100 km
horizontal resolution
Advantage: mediumrange forecasting (up to
72 hours)
One of the oldest
operational models
Data results available
mostly in MOS (model
output statistics) format
May, 2002
http://weather.unisys.com/aviation/index.html
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Prediction
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MM5
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Fifth generation mesoscale
NWP
Study types
– hurricanes
– cyclones
– monsoons
– fronts (formation,
interactions)
– land-sea breeze
meteorology
– urban heat islands
– mountain-valley
circulations
May, 2002
http://rain.mmm.ucar.edu/mm5/
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Prediction
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Sample Prediction
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Question: assuming
precipitation, what will it be?
Tools:
– Atmospheric sounding
(weather balloon data)
• Shows temperature
and dewpoint
temperature from
surface to upper
atmosphere
– Flowchart: precipitation
type decision tree
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Analysis/solution shown on next
slide
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Sample Prediction Solution
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Classroom Integration Forecasting Rules of thumb
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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
south
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Classroom Integration Weather observations
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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
May, 2002
http://www.shodor.org/bob2/wx/weather predict.html
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Prediction
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Classroom Integration
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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
May, 2002
http://www.emc.ncep.noaa.gov/mmb/meteograms/
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Prediction
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Classroom Integration
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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
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Prediction
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Questions?
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Chat Sessions
– Monday, May 13 3:304:30 PM and 6:00-7:00
PM
– Wednesday, May 15 3:304:30 PM
– Monday, May 20 6:007:00 PM
– Thursday, May 23 3:304:30 PM and 6:00-7:00
PM
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