Temperature Prediction
ASOS Temperature/Humidity
Senor
Why Can’t Use Model Output
Directly for Temp Forecasts?
• Model surface/2m height may be very
different than real elevation due to limited
horizontal/vertical resolution.
(e.g., MM5 36 km surface elevation for
Boeing Field is 256 m, should be 5 m)
• Model resolution may be inadequate to
properly simulate the temperature effects of
important features such as:
– Narrow gaps, such as the Fraser River Valley or
the Columbia River Gorge.
– Land/water contrasts, such as around Puget Sound
or along the coast.
Near Sea Level Gap
On Border of WA and OR
Portland wind distribution for all
days by direction and speed
• Wintry precipitation at PDX
– Almost exclusively E or SE
– Tendency towards E for snow and
SE for freezing rain
Wind
distribution
for days with
snowfall
Wind
distribution
for days with
Freezing
Rain
December 11-15, 2000 Case Study
• Strong winds for nearly four days
– Gale force a times
• Wintry mix in Western Gorge
and exit area.
– Little snow accumulation but
significant icing.
• Selected because:
– Data availability was good (esp.
ACARS)
– Model Initialization ok
Domain
Definition
36 km grid spacing
12 km grid spacing
Portland
The Dalles
Portland
The Dalles
Pass Height = 700 m
Pass Height = 600 m
4 km grid spacing
Portland
Cascade
Locks
The
Dalles
Pass Height = 400 m
12 km grid spacing
Portland
The Dalles
Pass Height = 600 m
1.33 km grid spacing, Pass Height = 150 m
•
Portland
Cascade Locks
Troutdale
The Dalles
444.4 m grid spacing, Pass Height = 100 m
Portland
Troutdale
Cascade Locks
T on
150 m
Surface
Portland
Troutdale
• Model temperatures may be seriously in error due
to poor model physical parameterizations, such as
for the planetary boundary layer, radiation, surface
energy fluxes, cloud and precipitation processes.
– Example: overmixing in PBL can result in the inability
to maintain shallow cold air masses.
– Example 2: improper soil moisture (too warm or dry)
can greatly influence temperatures.
• As a result of such errors, models can have serious
systemic temperature biases.
Shallow Fog…Nov 19, 2005
• Held in at low levels for days
• MM5 held in the inversion…generally
without the shallow mixed layer of cold air
a few hundred m deep
• MM5 could not maintain the moisture at
low levels
Temperature Biases
• Large temperature biases can occur at
certain times:
– When there is a shallow layer of cold air (few
hundred m deep) that is mixed out.
– During transition season (particularly spring,
when land surface conditions are problematic)
– During summer during warm periods.
00 UTC
12 UTC
Downslope Warming
• Large warming during downslope flow
• Often large over Cascade foothills (North Bend),
but apparent all over the world, including to the
lee (east) of the Rockies--the Chinook Wind.
• In Europe called the Foehn Wind.
• Uusually, air comes from mid-levels where
potential temperature is higher than at the surface.
A drop in dewpoint usually accompanies it.
Diabatic Effects
Diabatics
• Radiation:
– direct radiational heating and cooling of the air is
relatively small
– indirectly, very large through modulation of
ground temperature and communication into the
boundary layer by turbulence. Surface heating by
the solar flux and nighttime cooling by IR flux
dominate surface temperatures.
– Clouds have a major effect on radiational
heating/cooling.
Clouds, Radiation and Surface
Temps
• Clouds lessen warming during day by
lessening solar radiation
• Clouds decrease cooling at night by
intercepting IR radiation and reradiating
IRback to the surface.
• Thin cirrus…only minor influence (1-2F)
• Thick altostratus--5-10F influence or more.
IR Opacity of Air Can Influence
Surface Temps
• IR opacity is proportional to humidity.
• Increased water vapor content increases
opacity--better absorption and emission in
IR.
• Less water vapor results in better IR cooling
under clear conditions. That is why deserts
cool very rapidly at night. Why Washington
DC stays hot all night.
Conduction and Turbulence
Effects in the BL.
• Snohomish, WA
• April 4, 2005
SE Everett
Hoquiam, WA: July 15, 2002
18
70
Wind Speed (kts)
Temperature (ЎF)
16
65
12
60
10
55
8
6
50
4
45
2
0
40
1
2 3
4 5 6
7
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Hour (LDT)
Temperature (ЎF)
Wind Speed (knots)
14
Comparison of the daily temperature cycle between
observations (blue dashed) and the model (red triangles) for a
coastal location (Boston, MA) on 10 August 1997 impacted by
the passage of a sea breeze front.
2-m air temperature and 10-m wind
velocity in the afternoon of a sea breeze
event on April 18, 2005. The land-sea
temperature contrast drives the onshore
sea breeze. Local spatial variations in
sea surface temperature (SST) can
leave a signature on the sea breeze,
especially when complex coastlines
create multiple sea breeze fronts (e.g.,
the sea breeze penetrating from Long
Island Sound in the image above).
In our multiply-nested COAMPS
simulations, nest 4 (1.33 km resolution)
and nest 5 (0.44 km resolution) were
enhanced to account for urban effects
and to include time-varying (hourly)
high-resolution SST's from Alan
Blumberg's New York Harbor Observing
and Prediction system (NYHOPS). The
diurnal heating of the ocean surface is
thus represented in our simulations.
We are in the process of quantifying the
impact of these effects on the sea
breeze circulation for several distinct
events, and evaluating the forecast skill
of the system.
Southerly Buster…SE Australia…just like the push
MOS Compared to the NWS: Temperature
Cool Season Mi. Temp – 12 UTC Cycle
Average Over 80 US stations
7
6
5
4
3
2
'66-67 '71-72 '76-77 '81-82 '86-87 '91-92 '96-97 '01-02
Cool Season
24-h GUID.
24-h LCL
48-h GUID.
48-h LCL
Temperature
MAE (F) for the seven forecast types for all stations,
all time periods, 1 August 2003 – 1 August 2004.
Large one-day temp changes
MAE for each forecast type during periods of large temperature
change (10F over 24-hr), 1 August 2003 – 1 August 2004.
Includes data for all stations.
MAE for each forecast type during periods of large
departure (20F) from daily climatological values,
1 August 2003 – 1 August 2004.
Number of days
each forecast is the
most accurate, all
stations.
In (a), tie situations
are counted only
when the most
accurate
temperatures are
exactly equivalent.
In (b), tie situations
are cases when the
most accurate
temperatures are
within 2F of each
other.
Looser Tie Definition
Number of days
each forecast is
the least
accurate, all
stations.
In (a), tie situations are
counted only when the
least accurate
temperatures are exactly
equivalent. In (b), tie
situations are cases when
the least accurate
temperatures are within
2F of each other.
Looser Tie Definition
Highly correlated time series
Time series of MAE of MAX-T for period one for all stations, 1 August
2003 – 1 August 2004. The mean temperature over all stations is
shown with a dotted line. 3-day smoothing is performed on the data.
Cold spell
Time series of bias in MAX-T for period one for all stations, 1
August 2003 – 1 August 2004. Mean temperature over all
stations is shown with a dotted line. 3-day smoothing is
performed on the data.
MAE for all stations, 1 August 2003 – 1 August
2004, sorted by geographic region.
MOS Seems to have the most problems at high elevation stations.
Bias for all stations, 1 August 2003 – 1 August 2004,
sorted by geographic region.
Precipitation Comparisons
Brier Scores for Precipitation for all stations for the entire
study period.
Brier Score for all stations, 1 August 2003 – 1 August
2004. 3-day smoothing is performed on the data.
Prob. Of Precip.– Cool Season
(0000/1200 UTC Cycles Combined)
0.7
Brier Score Improvement over Climate
0.6
Guid POPS 24 hr
Local POPS 24 hr
Guid POPS 48 hr
Local POPS 48 hr
0.5
0.4
0.3
0.2
0.1
0
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