Transcript AOSC200_summer_lect11 - Atmospheric and Oceanic Science

AOSC 200
Lesson 11
LAND AND SEA BREEZE
– During the day, the land heats up quickly, while the
ocean heats up slowly
– The higher temperatures over land create lower
pressure at the surface and the lower temperatures
over the ocean create higher pressure at the surface
– This produces a pressure gradient from the ocean to
the land
– The wind flows from the sea to the land – this is
known as the sea breeze
– At night, this process reverses, and the land cools
more quickly than the ocean. This creates an area of
lower pressure over the sea, and an area of higher
pressure over the land
– The wind then flows from the land to the sea – this is
known as the land breeze
Sea breeze over Florida.
• In Florida we can have two sea breezes
which come from the two land/sea
interfaces on either side of the peninsula.
• These sea breezes will converge at the
center of the pensinula and produce clouds
and thunderstorms.
• The thunderstorms occur at the hottest time
of the day i.e. about 4 in the afternoon.
LAKE BREEZE
– The Great Lakes are a large enough body of
water to cause the sea breeze effect to take
place
– This is called the lake breeze
Lake breeze on Lake Michigan, July 13, 2000.
Fig. 12.10
Mountain and Valley Breeze
MOUNTAIN AND VALLEY
BREEZE
• During the day, the slopes of the mountain heat
up more quickly than the valley floor
• Like the sea breeze, the flow goes from higher
pressure and cooler temperatures (the
valley/sea) to lower pressure and warmer
temperatures (the mountain slope/land)
• Valley breeze
• At night, the mountain slopes cool more
quickly than the valley floor, and the winds
reverse – this is the mountain breeze
As the valley breeze forms during the day and forces the
air upwards, the moisture that rises can condense and
form clouds.
Mountain windstorms
• They occur most often in the winter when the
contrast in temperature between the mountain and
the valley is large.
• The example shown previously is a Katabatic
wind and occur all over the world. In the US we
see them in Colorado and the Columbian river
valley.
• In Boulder, Colorado these winds are funneled
down a mountain pass and become severe at the
bottom, up to 160 km per hour (100 mph).
Boulder Windstorm. See next slide.
Winds in the Boulder, CO, windstorm of February 2, 1990
Fig. 12.14
http://www.youtube.com/watch?v=
sjH0J9D92_Q
http://www.youtube.com/watch?v=
sjH0J9D92_Q
Fig. 12.4
MICROBURSTS
• Microbursts are small scale (<4km), intense
downdrafts
• They can sometimes be caused by the
evaporation of rain below a thunderstorm
• This creates cold, heavy air, which then plunges
to the Earth’s surface, where it spreads
outward and upward
• The intense winds last ~10 minutes, and can
cause as much damage as a small tornado
• In the past, microbursts have been the cause of
deadly airplane crashes while taking off and
landing
• Now, airports have microburst detectors
CHINOOK WINDS
• These occur along the eastern edge of the Rocky
Mountains, where the mountains meet the flatlands
• When air from the west hits the mountains, it is lifted
up over the Rockies
• As the air is lifted, it loses much of it’s water vapor
• When the air descends on the other side, it has little to
no moisture in it, and as it sinks, it compresses and
heats
• The dry, warm wind that results is called a Chinook (
snow eater)
• In 1943, near Rapid City, SD, a chinook raised the
temperature from -4oF to 45oF in two minutes!
SANTA ANA WINDS
• Has similar characteristics to a chinook
• These winds form when an anticyclone is
present over the Rockies – most common in the
fall
• The high pressure system forces already dry air
from the mountains, down to the western coast
• The Santa Ana winds create a serious fire
hazard, due to the warm temperatures and low
humidity
Fig. 12-17, p. 368
Santa Ana winds – cause and effect
DERECHOS
• A derecho is an hours-long windstorm that can
have winds up to 150 mph
• Occurs in the mid-west.
• It comes about when a strong summertime jet
stream is above a line of severe thunderstorms
formed by a stationary cold front
• The strong, cold downdrafts of the
thunderstorms can drag down the high speed
air from above
Fig. 12.11
Radar image of a Derecho moving through lower Michigan,
May 31, 1998
Number of derecho storms occurring from 1994 to 2003
Fig. 12-9, p. 360
WEATHER FORECASTING
• FOLKLORE
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Red sky at night, shepherd’s delight,
Red sky in morning, shepherd’s warning
When spiders’ webs in air do fly
The spell will soon be very dry
• PERSISTENCE
– The weather tomorrow will be the same as the weather today (two
times out of three)
• CLIMATOLOGY
– This takes persistence one step further
– The average weather say for a particular month is the same each year *
• ‘COLD in December – HOT in July’
– English saying:
• In July the Sun is hot,
Is it raining? No it’s not.
Fig. 13-1, p. 375
Climatology Forecast of a White Christmas
TREND AND ANALOG
• We know that persistence forecasts will eventually be wrong
because weather does change.
• A trend forecast assumes that the weather-causing patterns
are themselves unchanging in speed, size, intensity, and
direction of movement (this is called steady-state).
– For instance: we know that an approaching cyclone will bring rain
(weather does change) but assume that the amount of rain or its speed
will not change during all the path the cyclone will travel.
• The analog forecast also acknowledges that weather changes,
but unlike the trend method, it assumes that weather patterns
can evolve with time.
– The main assumption is that weather repeats itself.
– Therefore, this method “searches” for past weather patterns that are
similar (analog) to the current situation.
– In this sense, the future weather patterns “should” be similar to those
that happened in the past.
Trend forecast based on
the assumption that a midlatitude cyclone moves up
the East coast unchanged.
Fig. 13-3, p. 378
The D-Day Forecast: June 1944
– Suitable weather for the invasion:
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Initial invasion around sunrise
Initial invasion at low tide
Nearly clear skies
At least 3 miles of visibility
Close to full Moon
Relatively light winds
Non-stormy seas
Good conditions persisting for at least 36 hours, preferably for 4
days
– Three meteorology groups worked independently:
• Analog forecast
• Bergen Schools: air masses, cyclones and upper level patterns
• Waves forecast
Weather patterns leading up to D-day
The D-Day Forecast: June 1944
– First question: What are the odds, month-by-month, that
the weather required for the invasion would actually occur?
• May: 24-to-1
• June: 13-to-1
• July: 33-to-1
– However, the weather changed from a placid and calm May
to a very stormy June. A winter-like pattern not seen in the
Atlantic in June in past forty years!
– At the beginning the invasion was planned for June 5th but
postponed to the 6th due to the weather forecast. This
decision turned out to be correct!
NUMERICAL WEATHER
PREDICTION
• Step One: Weather Observations
Surface observations, Rocket and balloon
observations, Satellite observations
• Step Two: Data Assimilation
• Model grid and grid points
• Measurements do not cover all of the globe and are
not at set grid points
• The input data need to be interpolated, smoothed and
filtered. This process is called Data Assimilation
Data Assimilation
Water vapor image
NUMERICAL WEATHER
PREDICTION
• Step Three: Forecast Model Integration
• The measured data (initial conditions) and the “primitive
equations” of the atmosphere are used to forecast what the
status of the atmosphere will be in the future. In order to get a
“good” (accurate and precise) forecast enormous
computational resources are needed
• Step Four: Tweaking and Broadcasting
– Current forecasts do not sample the atmosphere on a grid
size that picks local events or resolve small scale
phenomena
• Local forecasters use local knowledge and experience to tweak
the final forecast for the public
Fig. 13.9
Concept of a stretched-grid model
Fig. 13.13
Richardson’s Model Grid
Numerical Weather Prediction Models
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Short-Range Forecast Models
US government uses two models for this purpose
ETA model – Run four times per day
Rapid Update Cycle (RUC) model– Run every three
days
• Forecast out to 48 hours
• Medium-Range Forecast Models
– Spectral-models
– Medium range Forecast (MRF) model
• Forecast out to 10 days
Numerical Weather Prediction
Models
• Why Do Forecasts Still Go Wrong Today?
• Imperfect data
• Models cannot solve small scale phenomena:
parameterization*
• Chaos: The atmosphere could react very
differently to slightly different initial conditions
(non-linear system) – butterfly flapping its wings.
• Is there any solution?
• Ensemble forecast
• Vary initial conditions*
• Use different models
Forecasting
• Let’s consider a car that travels at constant speed v
from point B towards point C
• We can use the equation
x = x0 + vt
(1)
to determine its location (the distance x) at a given
time t. x0 is the distance from point A to point B at
t=0
Forecasting
•  INITIAL CONDITION
• This equation comes from a MODEL or
idealization of reality.
• If for any reason x0 is NOT well known, or
there is an “error” in determining the exact
location of B, then the equation will give us
a different distance to point C
Forecasting
If we now ask the driver “to go straight” but we don’t give
him/her any point of reference (there is no road, trees or
anything to use as a reference), the final path could be not as
straight as the driver might think
Numerical integration takes one small step at a time to move
forward
Ensemble Forecast