AOS 452 Lab 1: Meteorological data decoding and forecast preparation
This semester we will be using a variety of programs and software specific to meteorology. The
first program we will focus on is:
THE “WEATHER” PROGRAM
5
0
45 a -variety of text weather data, including
The weather program is a valuable tool for viewing
4
3 Service forecasts. You will find the
station observations, model output, and National
1
0 Weather
weather program to be particularly useful in preparing9your National Collegiate Weather
3 forecasts. I have provided a handout
Forecasting Contest (NCWFC, often shortened to NFC)
which gives an overview of some of the commands typically used within the weather program.
Please take some time and look over this handout to get an idea of some of the commands you
may wish to use. For even further assistance, visit the weather program user’s guide at the
following URL: http://www.rap.ucar.edu/staff/pneilley/weather/guide.html.
To start the WEATHER program, type weather at the UNIX prompt.
The first thing we may wish to look at is the latest hourly observation for a particular station such
as Madison, WI. In order to do this, we will need to know the three-letter identifier of the
station. One of the sub-commands in the weather program is stations, so within the weather
program, type /stations. The backslash indicates that you are entering a sub-command into the
weather program. Once the new prompt appears, type @wi to get a listing of station identifiers
for the state of Wisconsin, and look for Madison. Try finding some of the three letter identifiers
for other cities around the United States by doing a search by state.
In order to view surface observations in the weather program, the metar sub-command must be
used. After typing /metar within the weather program, the station and time need to be entered
for the surface observation desired. There are several ways to specify a specific time or set of
times for listing observations. Here are some examples:
msn l
grb t
mke y
eau n
rst 6z-
the latest observation for Madison
all observations for Green Bay taken today (from 0000 UTC until now)
all observations for Milwaukee taken yesterday
give the last n hours of observations for Eau Claire, WI; where n is an
integer number of hours
all observations for Rochester, MN including and since 0600 UTC today
Experiment with the above examples to list various METAR reports. In addition, particular
dates and times can be specified. See the quick guide handout or the user’s guide online for
more information. The information included in the METARs will be discussed in further detail
later in this lab.
NOTE: A menu-driven format of the weather program is also available on the Room 1411
workstations. After typing weather to start the weather program, type line. A menu will appear
with five choices. To select a particular choice, simply type in the number next to the option you
want and press ENTER. To move back a menu in this version of the weather program, press
ENTER without entering any characters. Some of you may prefer this version of the weather
program compared to the version discussed earlier.
DECODING METARs (SURFACE OBSERVATIONS)
Our code-cracking escapade will begin with tackling the international standard code format for
hourly surface weather observations, METAR (For you trivia buffs, the METAR acronym
roughly translates from French as Aviation Routine Weather Report). Most METARs contain
essential data for pilots such as temperature, dew point temperature, sea level pressure, cloud
cover, wind direction and speed, visibility, the time the observation was taken, and any recorded
precipitation that may have fallen. All of this information is reported hourly from surface
stations around the world. These surface observations are typically taken within 10 minutes
before the top of the hour. For example, the 1300 UTC observation may be taken at 1253 UTC.
So, when looking for a particular hourly observation, you need to look for the observation taken
between **50 and **00. However, special observations are taken at any time (in between hours)
if weather conditions that may be important to pilots change, such as visibility, falling
precipitation or cloud cover.
Standards have been set in order to distribute all of this information in a compact format. A key
to decoding METARs has been provided in a handout. The following is an example of a
METAR:
KMSN 190553Z 25003KT 10SM OVC060 17/14 A2992 RMK AO2 RAB06E53 SLP130 P0001
60001 T01670139 10206 20161 402500100 56002
Follow along with each piece of information as this observation is decoded. This is a METAR
taken from KMSN (Madison, WI) at 0600 (0553) UTC on the 19th of the month. The prevailing
wind was from 250 degrees (from the west-southwest) at 3 knots. Visibility was recorded to be
10 (statute) miles. The sky cover was overcast, with cloud height at 6,000 feet. The temperature
to the nearest whole degree was 17 degrees Celsius, and the dew point temperature to the nearest
whole degree was 14 degrees Celsius. The altimeter recorded an observation of 29.92 inches of
mercury. RMK stands for remark, and AO2 is the type of automated station. Rain began falling
at 06 minutes past the hour (at 0506 UTC) and ended at 53 minutes past the hour (at 0553 UTC).
The sea level pressure was recorded to be 1013.0 mb. There was .01 inches of precipitation
recorded in the last hour, and .01 inches of precipitation fell in the last 6 hours. The temperature
was 16.7 degrees Celsius, and the dew point temperature weas 13.9 degrees Celsius. The highest
temperature in the previous 6 hours was 20.6 degrees Celsius, and the minimum temperature in
the previous 6 hours was 16.1 degrees Celsius. The maximum (minimum) temperature for the
24-hour period was 25.0 (10.0) degrees Celsius. The pressure was decreasing, then became
steady, and fell 0.2 mb over the last 3 hours.
Note that for sea level pressure a three digit shorthand is transmitted. For example, a report of
SLP113 refers to a sea level pressure of 1011.3 mb. Another example would be SLP998,
referring to a sea level pressure of 999.8 mb. The leading “9” or “10” is omitted from the
observation, as well as the decimal point between the last two digits. As a general rule, if the
first digit in the SLP group is a 5 or greater, then add the beginning “9” to the observation. If the
first digit is less than a 5, then add the beginning “10” to the observation. This will hold true
except in extreme cases. For example, the highest recorded sea level pressure was 1083.6 mb in
Russia in 1968. In this case, a reading of SLP836 would be tricky to decode without additional
information, since the rule states that this would be a reading of 983.6 mb.
If you want a more in-depth look at METAR decoding, visit the following URL:
http://www.met.tamu.edu/class/METAR/metar.html. The official guide to METAR code is
chapter 12 of Federal Meteorological Handbook No. 1, which can be found online at
http://www.mrx.net/weather/fmh1/fmh1ch12.htm.
Below is a table of the information described by the second character of the pressure tendency
group (the “5” group):
Table: Characteristics of Barometer Tendency
Primary
Requirement
Description
Code
Figure
Increasing, then decreasing
0
Increasing, then steady, or increasing then increasing more slowly.
1
Increasing steadily or unsteadily.
2
Decreasing or steady, then increasing; or increasing, then increasing more rapidly.
3
Increasing, then decreasing
0
Steady
4
Decreasing, then increasing.
5
Decreasing, then increasing.
5
Decreasing then steady; or decreasing then decreasing more slowly.
6
Decreasing steadily or unsteadily.
7
Steady or increasing, then decreasing; or decreasing then decreasing more rapidly.
8
Atmospheric
pressure now
higher than 3
hours ago.
Atmospheric
pressure now
same as 3 hours
ago.
Atmospheric
pressure now
lower than 3
hours ago.
STATION MODELS
Weather observations are taken several times each day at thousands of locations over the world.
Meteorologists need a way to get the detailed information collected into the smallest area
possible on a weather map so that several stations can be plotted for the same observation time
on the same map, thus giving the "big picture" of what the weather is doing at a particular
moment in time. Weather conditions observed at a particular location are best represented on a
map using station models.
A station model can depict several weather variables, including temperature, dew point
temperature, current weather conditions, cloud cover, wind speed, wind direction, visibility, and
atmospheric pressure (surface observations) or height (upper air observations). It will be to your
benefit to become familiar with station models as you will see them in map discussions and case
study projects. If you not familiar with station models or just need a refresher, take a look
through the handout passed out during class as well as the following web sites:
http://cimss.ssec.wisc.edu/wxwise/station/
-- Guide on surface station models
http://ww2010.atmos.uiuc.edu/(Gh)/guides/maps/sfcobs/home.rxml
-- Another guide on surface station models
http://ww2010.atmos.uiuc.edu/(Gh)/guides/maps/upa/home.rxml
-- Guide on upper air station models
Examples of station models
Upper air
Surface
-25
542
-40
DECODING NWP MODEL OUTPUT
In addition to surface observations, the weather program is a useful way to access numerical
weather prediction (NWP) model output. Many of you likely are familiar with some of the
operational models such as the Eta, the Nested Grid Model (NGM) and the Global Forecast
System (GFS; a combination of the old Aviation [AVN] and Medium Range Forecast [MRF]
models). The output from these models can be useful in providing guidance while preparing a
forecast. However, one must be extremely careful not to follow model guidance blindly, as that
could certainly lead to poor forecasts.
There are three types of model output you will learn to decode: FOUS (raw model output data),
EXT (extended model output data), and MOS (model output statistics). Handouts have been
provided to help you in decoding each type of data. Most model data are available in 12-hour
increments (at 0000 UTC and 1200 UTC), and some of the model data are now available in more
frequent time increments (such as six hours for the GFS model and hourly for the RUC [Rapid
Update Cycle] model).
FOUS
One form of coded model data is FOUS (Forecast Output United States). This product takes
forecast information directly from the model output and displays the information in a compact
manner. The forecasts are provided in six-hourly intervals from 6 to 48 hours after either 0000
or 1200 UTC. Information given includes six-hour accumulated precipitation, relative humidity,
vertical velocity, lifted index, sea level pressure, direction and speed of the mean wind in the
boundary layer, 1000 to 500 hPa thickness, and three model-layer temperatures. FOUS is
generally found to be most useful in precipitation forecasting. The general format for the raw
data can be found below, and a sample can be found in a separate handout.
The general format:
-----------------FOXXII KWBC DDTTTT
TTPTT R1R2R3 VVVLI PSDDFF HHT1T3T5
---------------------------------NNN// R1R2R3 VVVLI PSDDFF HHT1T3T5
06PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
12PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
18PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
24PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
30PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
36PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
42PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
48PTT R1R2R3 VVVLI PSDDFF HHT1T3T5
CODE
=====
XX
II
DD
TTTT
NNN
PTT
R1
R2
R3
VVV
LI
PS
DD
FF
HH
T1
EXPLANATION
==================
Region identifier.
Station group number.
Day of the month forecast was issued.
Greenwich time of forecast cycle on which the data is based.
Forecast station three letter identifier.
6 hour accumulated precipitation in hundredths of inches.
Mean relative humidity of the lowest model layer (lowest 35
mb), in percent.
Mean relative humidity of model layers 2 through 9 (up to 500
mb), in percent.
Mean relative humidity of model layers 10 through 13 (500 to
200 mb), in percent.
Vertical velocity at 700 mb, in tenths of a microbar per
second, weighted average of three hourly values at forecast
time, one hour before, and one hour after (double weighted
at forecast time). Minus sign represents downward motion.
Lifted index in degrees Celsius. Negative values are designated
by subtracting from 100; e.g. -4= 96. Taken from the lowest
(most unstable) of four possible values. The values derived
from lifting parcels from the four lowest model layers up
to 500 mb.
Sea level pressure calculated from lowest sigma level (based on
the contour base map).
Direction in tens of degrees of the mean wind in the lowest model
layer (35 mb).
Wind speed in knots of the lowest model layer (lowest 35 mb).
1000-500 mb thickness in decameters with the first digit omitted.
Temperature in model layer 1 (lowest 35 mb) in degrees Celsius.
T3
T5
Temperature in model layer 3 (approximately 900 mb).
Temperature in model layer 5 (approximately 800 mb).
FOUS data are available from the NGM and Eta for a select number of cities in the United
States. The sub-commands in the weather program for these products are /ngm and /eta.
EXT
The extended model data (EXT) format is similar to FOUS data, but is shown in an easy to read,
tabular format. Here is a sample (for Albany, NY at 0000 UTC 28 August 2002):
Station: ALB
Lat: 42.75 Lon: -73.80
Initialization Time: 02-08-28 0000 UTC
PARAMETER/TIME
000
006
012
------------------- ------ ------ -----DAY / HOUR
28/00 28/06 28/12
------------------- ------ ------ -----TEMPS
1000 MB (C)
21
16
13
850 MB (C)
12
11
10
700 MB (C)
7
7
7
500 MB (C)
-11
-11
-12
1000-500 THCK
5681
5659
5640
Elev:
92
Closest grid pt: 22.3
018
-----28/18
------
024
-----29/00
------
030
-----29/06
------
036
-----29/12
------
20
9
6
-11
5653
20
9
6
-11
5649
16
10
5
-10
5645
15
10
4
-10
5639
042
------ 29/18
------ 21
11
5
-10
5665
MOISTURE
1000 MB DP(C)/RH
9/47
8/61
8/74
9/51 10/51 10/64
9/70 10/47
850 MB DP(C)/RH
6/69
5/68
4/69
3/66
1/57 -6/30 -8/27
0/48
700 MB DP(C)/RH
-17/16 -20/13 -23/10 -23/10 -18/17 -9/34 -5/53 -2/63
500 MB DP(C)/RH
-25/30 -23/36 -19/54 -17/66 -11/98 -11/97 -11/91 -14/72 PRCPABLE WTR (IN)
0.80
0.75
0.77
0.82
0.89
0.88
0.93
1.03
CONV PRECIP (IN)
0.03
0.12
0.05
0.00
0.00
0.00
0.00
TOTAL PRECIP (IN)
0.22
0.39
0.07
0.01
0.00
0.00
0.00
WIND DD/FFF (Kts)
1000 MB
850 MB
700 MB
500 MB
250 MB
02/012
03/009
02/006
36/002
24/059
PRESS/HEIGHTS
MSL PRESSURE
850 MB HGT
700 MB HGT
500 MB HGT
250 MB HGT
1023.0 1026.7 1029.1 1028.8 1028.1 1027.8 1028.3 1025.6
158
159
160
162
161
160
160
160
319
320
321
322
321
320
320
320
587
588
588
589
588
587
587
587
1084
1085
1083
1085
1084
1083
1083
1084
VERTICAL VEL (uB/S)
850 MB
700 MB
500 MB
OTHER
TROP PRES (MB)
500 MB ABS VOR ()
1000 MB LI (K)
149
8.3
281
06/018
09/008
04/004
14/002
24/060
08/011
11/008
08/008
09/004
23/052
09/006
08/007
12/007
14/011
23/051
12/013
11/011
12/008
19/008
24/049
13/011
14/010
14/009
23/010
24/048
10/008
09/008
12/004
24/015
25/056
11/004
14/008
19/005
26/014
24/057
0
-6
0
-5
-1
-9
-4
2
-5
-5
-9
6
6
11
2
-3
-7
-8
2
-4
-4
152
8.4
286
153
9.7
287
150
10.3
281
152
12.4
281
155
14.2
285
155
11.8
286
154
11.5
281
As you can see, the extended data are easy to decode. Note that the precipitation numbers will
include only the precipitation that is forecast to fall in the forecast increment (for this example,
the 6 hour period) just like FOUS. Also note that for the wind forecast, the direction is given
first (simply add a zero to get the direction from which the wind is forecast to come), and the
speed is given second in knots. If you should have any more questions regarding the extended
model output, feel free to ask.
Example sub-commands in the weather program for these products include /extavn, /extngm,
and /exteta.
MOS
Another form of coded meteorological data found in the weather program is model output
statistics, or MOS. The MOS products are a bit different than the aforementioned model
products, as they take into account past model performance, model biases, and other model
statistics. The MOS output includes forecasts for three- and/or six-hourly temperature and dew
point temperature, maximum and minimum temperature, cloud cover, surface wind, precipitation
probability, visibility, and sometimes a variety of other products. The MRF MOS numbers are
available once daily (0000 UTC), the NGM and Eta MOS numbers are available twice daily
(0000 and 1200 UTC), and the AVN MOS numbers are available four times daily (0000, 0600,
1200, and 1800 UTC).
A sample MOS product from the Eta is given below:
KMSN
ETA MOS GUIDANCE
DT /AUG 26/AUG 27
HR
18 21 00 03 06 09 12
N/X
60
TMP 87 90 85 75 69 64 62
DPT 72 70 70 68 63 59 57
CLD SC SC SC CL CL CL CL
WDR 32 31 33 02 36 01 01
WSP 06 04 02 04 04 04 04
P06
14
5
10
P12
12
Q06
0
0
0
Q12
0
T06
23/19 9/11 3/ 0
T12
26/19
8/26/2003 1200 UTC
/AUG 28
15 18 21 00 03 06 09 12
81
55
72 78 79 73 62 58 57 59
59 55 54 55 54 53 53 55
CL CL CL CL CL CL CL SC
03 03 04 07 08 09 09 12
07 07 07 06 04 03 04 05
2
2
2
8
4
8
0
0
0
0
0
0
1/ 0 0/ 4 0/ 0 4/ 1
4/ 1
1/ 4
/
15 18 21 00
79
70 76 78 74
60 63 63 63
SC SC SC SC
14 15 16 13
12 09 09 09
10
14
18
0
0
0
7/ 1 12/15
9/ 3
A handout has been provided with information to decode the MOS product. Much of the
information is self-explanatory (e.g., temperature, dew point, etc.). The values in a certain
column represent the statistically derived forecast values at that time for a specific variable.
Links to decoding MOS data can also be found on UW-Madison’s NFC page:
http://www.aos.wisc.edu/~nfc.
The sub-commands in the weather program for these products are /ngmmos, /newavnmos,
/mrfmos, and /etamos.
Blindly following what the model statistics show will lead to large forecast errors, so do not get
in the habit of “MOScasting”. If you have thoroughly analyzed the weather situation and came
up with temperatures and precipitation values similar to the model output, you may have a higher
degree of confidence in your forecast.
Note that getting each type of output for a particular station is the same as for getting surface
observations. First you type the subcommand for the product that you wish to view, then get the
data using the same format as before:
msn 12z -- get the most current 1200 UTC product for Madison, WI
mke l -- get the latest product for Milwaukee, WI
FP4
In addition to model guidance, the National Weather Service issues numerical forecasts for
specific stations twice daily. Included are the day one to three temperature forecasts and
precipitation probabilities. The fp4 product appears as follows from the weather program:
dd/hhmm ppp wW tt1/tt2 tt3/tt4 tt5 ffPPP
dd = day
hhmm = hour and minute issued
ppp = place
wW = day1 and day2 weather type
ttn = temperature (day1 maximum, day1 minimum, etc...)
ff = forecaster id number
PPP = 12 hour period probability of precipitation in tens of percent
The following is an actual sample:
06/0926 FTW BT 077/058 082/064 077 10137
Here is the fp4 forecast decoded:
This forecast for Fort Worth, Texas was issued on the 6th of the month at 0926 UTC. The
weather for today is partly cloudy (B). The weather for tomorrow is thundershowers (T).
Today's high is forecast to be 77, and tonight's low 58. Tomorrow's forecast high is 82, while
tomorrow night's forecast low is 64. The high the following day is forecast to be 77. Forecaster
10 prepared this FP4. The precipitation probabilities are set at 10% for today, 30% tonight and
70% tomorrow.
A link to decoding the FP4 product can be found on the UW-Madison NFC web page. The subcommand in the weather program for this product is /fp4.
All of the aforementioned data will be useful in your forecast preparation during the National
Collegiate Weather Forecasting Contest (NCWFC). Everyone will have a different method for
forecasting, but it is important to at least look at all available data before making a final forecast.
We will ask that you keep a daily log of your forecast preparation. Actual guidelines for the
forecasting contest will be laid out separately from this lab exercise.
LAB ASSIGNMENT #1 (due Thursday, 9 September 2003)
1. On the base map provided, create a map of “current” surface observations for the following
stations: Miami, FL; Los Angeles, CA; Billings, MT; Norfolk, VA; Madison, WI; St. Louis,
MO; Atlanta, GA; and Flagstaff, AZ. First, you will need to find the three-letter identifier for
each station. Then, find the surface observation for each station for an hourly observation time,
and plot the sky cover, temperature (in degrees Fahrenheit), dew point temperature (in degrees
Fahrenheit), sea level pressure (using the three-digit shorthand), visibility, current weather, and
the surface wind (speed and direction) on the station model. You are free to choose any date and
time as long as all of the observations you record are from the same hourly observation time.
Also, please record whichever time you choose somewhere on the map. Please attach a text file
that includes all of the METAR reports you used. (Note: For the temperature and dew point
temperature, use the most precise value available in the METAR)
2. Using the log sheets provided, prepare a one-day forecast for two cities: Madison, WI and
Miami, FL. Prepare the forecast as if it were for the forecasting contest. Forecast the high
temperature, low temperature, and precipitation category for the 0600 UTC – 0600 UTC period
as outlined by the NFC guidelines. You may forecast on any day between Wednesday, 3
September and Saturday, 6 September 2003. Please provide your forecast, the two completed
forecast log sheets (including the actual forecast verification), and a brief discussion of the
quality of your forecast (in comparison with the verification).
Keep in mind that the forecasting contest begins on Monday, 15 September. This exercise will
give you a little preview of the procedure you will carry out when making your forecasts. Feel
free to ask questions if you have any.