This dataset contains one-minute resolution surface meteorological data in University Corporation for Atmospheric Research/Joint Office for Science Support (UCAR/JOSS) Quality Control (QC) format from stations within the following networks:
Section 2.0 contains a detailed description of the
instrumentation, siting, and algorithms used by the source network to collect
the data. Much of this information is taken from the individual network
webpages listed in each subsection below.
Section 2.1 contains a detailed
description of the format of the composite dataset. See
Section 2.2 for information on data processing, and
Section 3.0 for the quality control processing performed by UCAR/JOSS
on this dataset. Section 4.0 contains references.
The Automated Surface Observing System (ASOS) is an automated observing
system that is sponsored by the Federal Aviation Administration, National
Weather Service (NWS) and the Department of Defense (DOD). ASOS provides
weather observations which include: temperature, dew point, wind,
altimeter setting, visibility, sky condition, and precipitation.
ASOS stations are installed at airports throughout the country. All 309
stations that are in the BAMEX area of interest are included in this BAMEX
2003 One Minute Surface Composite.
The Automated Surface Observing Systems are designed to provide airport
weather observations in real time. The observing systems work nonstop,
updating observations every minute, 24 hours a day, every day of the year.
Aviation weather parameters are measured in the runway touchdown zone on
the airport.
The ASOS data were acquired by UCAR/JOSS for BAMEX via two methods.
Stations were downloaded from an NCDC FTP website once monthly during the
BAMEX TOI. Stations not available on the FTP site were acquired using a
modem and a dial-in telephone system. UCAR/JOSS typically called each
station every 8 hours. Note that there is a data gap in the dialed data
in early June, 2003. The data gap is the result of an emergency change by
NCDC in the passwords for dialing data, which caused the downloads to fail
until NOAA provided UCAR/JOSS the new passwords to access the data.
The ASOS uses a chilled mirror to determine the dew point
temperature. Once per day the mirror is heated to recalibrate
the reference reflection expected from a dry mirror (since a
clean mirror needs relatively less indirect light to determine
when dew has formed than a dry mirror). This procedure compensates
for a possible dirty or contaminated mirror and redefines adaptive
criterion value used to determine when dew or frost has occurred.
This once per day recalibration nominally takes about 15 min (
ASOS Users Guide, 1998
[ PDF]).
The occurrence time of this recalibration varies from station to station. Some
stations also vary the occurrence time of the recalibration on about weekly
intervals. In an effort to remove the most extreme effects of this
recalibration, for any occurrence of dew point temperatures 10 degrees F or more
higher than the one in the preceding minute, and when the dewpoint is also 1
degree F or more than the temperature at the present time, the dewpoint flag for
the preceding minute, the dewpoint flag for the present minute, and the dewpoint
flags for the next 6 minutes (clock time) were set to Bad by JOSS. Note that
this test applies to consecutive minutes, not obs. To test the first dewpoint
value after this spike, it was compared to the previous value even though the
previous one would have been set to Bad. If the dewpoint spike test failed, then
the dewpoint flags were set to Bad when the dewpoint was 1 degree F or more than
the temperature. The dewpoint values were not changed. This recalibration and
associated flagging of dewpoint spikes affects all ASOS stations.
There are three station pressures reported at most station for each time period.
All stations have at least two pressure sensors and the same methodology is
used for stations with two sensors as we use for stations with three sensors.
The lowest sensor pressure value obtained, whose pressure difference from
either of the other sensors is 0.04 inches or less, is the designated ASOS
pressure to be reported at the end of the minute. If no two sensors are within
0.04 inches of each other, then the station pressure is set to missing for that
time period. ( ASOS Users Guide, 1998 Section 3.3.2
[ PDF])
Pressures are reported in inches of mercury.
UCAR/JOSS converts the designated ASOS pressure to millibars and reports it in
this 1-minute surface composite.
All Automated Surface Observing System sites included in this composite
are commissioned.
For more information on ASOS data and instrumentation, see the
National Weather Service
Automated Surface Observing System web site (NWS,
2003),
Federal Aviation Administration Automated Surface Observing System web site
(FAA, 2004), and the
ASOS Users Guide, 1998
[ PDF].
Also see the ASOS Users Guide appendices, 1998
[ PDF] which
includes instrument specifications and frequencies.
For information on the calculation of parameters derived by UCAR/JOSS from the
raw parameters available, see Section 2.2.
The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM)
Southern Great Plains (SGP) Surface Meteorological Observation System
(SMOS) [ARMSFC] stations are located at many of the ARM SGP Extended
Facilities in southern Kansas and northern Oklahoma. There are 15 SMOS
station included within this BAMEX 2003 One Minute Surface Composite.
Instrumentation
The SMOS mostly uses conventional in situ sensors to obtain one-minute
averages of surface wind speed, wind direction, air temperature, relative
humidity, barometric pressure, and precipitation at the central facility
and many of the extended facilities of the SGP Clouds and Radiation Testbed
(CART) site. SMOSes have not been installed at extended facilities located
within about 10 km of existing surface meteorological stations such as
those of the Oklahoma MESONET.
The SMOS stations directly measure:
Wind speed at 10 m, Precision: 0.01 m/s; Uncertainty: +/-1% for 2.5 to 30
m/s (see Assessment of System Uncertainties for Primary
Quantities Measured
for wind speeds below 2.5 m/s)
Wind speed and direction sensor: Propellor anemometer and wind vane, R. M.
Young Model 05103 Wind Monitor
Wind direction at 10 m, Precision: 0.1 deg; Uncertainty: +/-5 deg
Wind speed and direction sensor: Propellor anemometer and wind vane, R. M.
Young Model 05103 Wind Monitor
Air temperature at 2 m, Precision: 0.01 C; Uncertainty: a function of wind
speed (see Assessment of System Uncertainties for Primary
Quantities Measured)
Temperature and relative humidity sensor: Thermistor and Vaisala RH,
Campbell Scientific Model HMP35C Temperature and Relative Humidity Probe
Relative humidity at 2 m, Precision: 0.1% RH; Uncertainty: +/-2.06% RH (0%
to 90% RH), +/-3.04% RH (90% to 100% RH)
Temperature and relative humidity sensor: Thermistor and Vaisala RH,
Campbell Scientific Model HMP35C Temperature and Relative Humidity Probe
Barometric pressure at 1 m, Precision: 0.01 kPa; Uncertainty: +/-0.035 kPa
Barometric pressure sensor: Digital barometer, Vaisala Model PTB201A
Precipitation, Precision: 0.254 mm; Uncertainty: +/-0.254 mm (unknown
during strong winds and for snow)
Precipitation: Electrically heated, tipping bucket precipitation gauge,
Novalynx Model 260-2500E-12 Rain/Snow Gage
The data logger is a Campbell Scientific Model CR10 Measurement & Control
Module and Model SM716 Storage Module, Precision: A function of input type
and range, Uncertainty: 0.2% of Full Scale Range for Analog Inputs
2.0 Detailed Data Description
2.0.1 Automated Surface Observing System (ASOS) Algorithms
2.0.2 DOE ARM SMOS Surface Meteorological Data (ARMSFC) Algorithms
| +/- 1% | for a reported wind speed from 2.5 to 30.0 m/s |
| -0.12 to +0.02 m/s | for a reported wind speed of 2.0 m/s |
| -0.22 to +0.00 m/s | for a reported wind speed of 1.5 m/s |
| -0.31 to -0.20 m/s | for a reported wind speed of 1.0 m/s |
| -0.51 to -0.49 m/s | for a reported wind speed of 0.5 m/s |
Wind Direction
The sensor accuracy is specified as +/-3 deg. The A/D conversion accuracy is equivalent to � 0.7 deg over a temperature range of 0 to 40 deg C for a period of one year. I have estimated sensor alignment to true north to be accurate within +/-3 deg. The uncertainty with 95% confidence is, therefore, approximately +/-5 deg.
Temperature
The accuracy of the temperature measurement is specified as +/-0.4 C. Included in this accuracy are sensor interchangeability, bridge resistor precision, and polynomial curve fitting errors. The long-term stability is not known. The radiation error of the naturally aspirated multi-plate radiation shield used for all stations, except for the central facilities SMOS, is specified as +/-0.4 C rms at 3 m/s, +/-0.7 C rms at 2 m/s, and +/-1.5 C rms at 1 m/s.
The uncertainty with 95% confidence of temperature sensors in naturally aspirated radiation shields is approximately:
| +/-0.45 C | when the wind speed is 6 m/s or greater |
| +/-0.89 C | when the wind speed is 3 m/s |
| +/-1.46 C | when the wind speed is 2 m/s |
| +/-3.07 C | when the wind speed is 1 m/s |
The radiation error of the aspirated radiation shield used at the Central Facility is specified as +/- 0.2 C rms. The uncertainty with 95% confidence of temperature sensors in this radiation shield is, therefore, +/- 0.57 C.
Relative Humidity
The accuracy of the sensor is specified as +/-2% RH for 0 to 90% RH, and +/-3% RH for 90 to 100% RH. Errors considered in this accuracy are calibration uncertainty, repeatability, hysteresis, temperature dependence, and long-term stability over a period of one year. The A/D conversion accuracy is equivalent to +/-0.5% RH.
The uncertainty with at least 95% confidence is, therefore,
| +/-2.06 % RH, 0 to 90 % RH |
| +/-3.04 % RH, 90 to 100 % RH |
The UNCERTAINTY of +/-2.06% RH (0% to 90% RH) or +/-3.04% RH (90% to 100% RH) is for a calibrated probe. The RH values reported by the probe normally drift slowly upward over time. Whenever a probe falls outside the range of uncertainty for a SIX-MONTH SENSOR VERIFICATION or reports values exceeding 104% RH, the probe is replaced by one that has been recently calibrated. Occasionally, a sensor will report values that are suspiciously low. A work order is then issued to perform a verification check and replacement if needed. A data quality report is issued for known erroneous data.
Barometric Pressure
The manufacturer's technical data contains an uncertainty analysis. Errors included in their analysis are linearity, hysteresis, calibration uncertainty, repeatability, temperature dependence, and long-term stability over a period of one year. Because the sensor has a digital output, no conversion error occurs in the Campbell data logger.
The specified uncertainty with 95% confidence is +/-0.035 kPa.
Precipitation
The tipping-bucket rain gauge produces a pulse output. The data logger counts the pulses for the period of integration. The uncertainty is, therefore, a minimum of one full bucket or 0.254 mm. For rain rates less than 75 mm per hour with light to moderate winds, the collection efficiency of the gauge is 99 to 100%. During heavy rain or strong, gusty winds, the collection efficiency is reduced. Manufacturers have not attempted to specify accuracies for these conditions.
Although Alter shields are used to increase the efficiency of snow collection, the efficiency of collection is variable and usually well below 100%. Furthermore, the heater does not melt snow at temperatures below -10 deg C. Thus the data user should use the water-equivalent estimates for snowfall with a great deal of skepticism. At best, the readings are only a rough indicator that snow occurred, for temperatures above -10 C. If snow occurred at -10 C or below and the temperature increased to above -10 C hours later, then some melting would occur and an incorrect time of precipitation would be reported.
Site maps are available at: http://www.arm.gov/sites/sgp/maps.stm (ARM, 2004d).
Algorithms
Description of System Configuration and Measurement Methods of all SMOS stations except at E21, Okmulgee, OK
The SMOS sensors are mounted on a 10 meter, triangular tower, except for the rain gauge.
The wind monitor propeller anemometer produces a magnetically controlled AC output whose frequency is proportional to the wind speed. The Wind Monitor direction vane drives a potentiometer, which is part of a resistance bridge. The Wind Monitor is mounted on a cross-arm at a height of 10 m.
The T-RH probe thermistor is part of a resistance bridge. The Vaisala RH circuitry produces a voltage that is proportional to the capacitance of a water vapor absorbing, thin polymer film. For all SMOSes except, the one at the central facility, the T-RH probe is mounted in a naturally aspirated R. M. Young Model 41002 Gill Multi-plate Radiation Shield. The central facilities (E13) T-RH probe is mounted in an R. M. Young Model 43408 Gill Aspirated Radiation Shield. The Radiation Shields are mounted at a height of 2 m on the southwestern leg of the tower.
The barometric pressure sensor uses a silicon capacitive pressure sensor and is housed in a weatherproof enclosure along with a data logger, a storage module, and serial communications equipment, all mounted on the tower at a height of 1 m.
The rain-snow gauge has a 12-inch orifice and is located near the tower. A thermostatically controlled heater melts frozen precipitation. The water is funneled to a tipping bucket, which triggers a magnetic reed switch. An Alter Shield is used to increase the reliability of rain collection in high winds and of snow collection.
The data logger measures each input once per second except for barometric pressure, which is measured once per minute. The data logger produces one-minute averages of wind speed, vector-averaged wind direction, air temperature, and relative humidity. The one-minute output includes the barometric pressure reading and total precipitation during the minute.
Description of SMOS at E21, Okmulgee, OK
The same sensors that are used on the other SMOS stations are used on the E21 SMOS. Since this SMOS is in a forested site, the sensors are mounted on a 20 m tower which extends above the top of the forest canopy. During the summer of 1999 the canopy height was estimated to be 47 feet or 14.3 m. The air temperature and relative humidity probe is mounted at 17.0 m or approximately 2.7 m above the average canopy height facing North. The wind speed and direction sensor is mounted at 18 m or approximately 3.7 m above the average canopy height on a boom 10ft out from the tower facing North. The barometric pressure sensor is mounted at 19 m or approximately 4.7 m above the average canopy height. New booms for sensor mounting were installed in July 2002. The two sensors affected are the wind speed and direction sensor and the T/RH probe. The height of the wind speed and direction sensor did not change, it is still 18 m or approximately 3.7 m above the average canopy height. The orientation of the wind speed and direction sensor did change and it is now facing West on a boom 15ft out from the tower. The date of the wind speed and direction sensor change was July 16, 2002 at 18:44 GMT. Both the orientation and the height of the T/RH probe changed. It is now 19.25 m above the surface or 4.95 m above the average canopy height and is facing Northeast. The date of the T/RH probe change was July 15, 2002 at 22:36 GMT.
Precipitation Measurements Questionable
Since the height of the tower at E21 extends above the forest canopy it has become a favorite roosting area for turkey vultures. The birds roosting on the tower has caused considerable amounts of bird droppings on the equipment, tower & sensors. The precipitation gage is frequently clogged with bird droppings during the time period that the vultures are in the area. The turkey vultures are migratory but are generally in the area from early April through sometime in November. Precipitation data during these times should be investigated closely to determine if the precipitation gage data is consistent with other nearby sites. Typically when the raingage is clogged a stairstep pattern in the data can be noticed.
Theory of Operations
Each of the primary measurements of wind speed, wind direction, air temperature, relative humidity, barometric pressure, and rainfall are intended to represent self-standing data streams that can be used independently or in combinations. The theory of operation of each of these sensors is similar to that for sensors typically used in other conventional surface meteorological stations. Some details can be found under Algorithms - Description of System Configuration and Measurement Methods but further, greatly detailed description of theory of operation is not considered necessary for effective use of the data for these rather common types of measurements. The SMOS instrument mentor or the manufacturer can be contacted for further information. Contact information can be found on the SMOS web page given at the bottom of this section 2.0.2.
Instrument Mentor Quality Control Checks
Data quality control procedures for this system is mature.
Graphical displays are generated at ANL and inspected on a weekly basis for the following parameters: relative humidity, temperature, wind speed, wind direction and barometric pressure. Any one of these parameters acquired on any one day for up to 4 SMOS stations are viewed on a single display to compare data from relatively close extended facilities. This procedure does not verify accuracy, but does help identify suspected drifts in the sensors. When any of the graphed data are suspect, a work request for investigation and/or sensor verification by SGP site operations personnel is issued. Every six months the aforementioned SMOS sensors are compared to secondary references. Given adequate funding, every two years the wind monitors are replaced and the removed sensors are returned to the manufacturer for preventative maintenance and, if necessary, re-calibration. Summary reports are sent weekly to the SGP site scientist team. Precipitation data are not visually inspected due to the site-specific nature of these parameters. It is left to the user to determine the validity and accuracy of these values.
Additional checks on the temperature and relative humidity probes, and rain gauges are accomplished every two weeks during routine maintenance. The temperature and relative humidity probes are compared to secondary standards (hand-held meters). The secondary standards are calibrated in a humidity generator chamber at the SGP facility every 7 to 10 days. The rain gauges are checked for proper operation, the screens are cleaned if necessary, and tip tests are done. The rain gauges are also inspected for being level and at the proper height for the Alter wind-screen. Adjustments are made at the time of inspection.
Data acquisition and processing is disabled whenever sensors are being tested.
One problem currently persists. The rain gauges on the SMOS and on the SWATS are tested biweekly. Data acquisition and processing can be disabled on the SMOS stations but not on the SWATS. Whether data acquisition and processing is disabled or false counts appear in the data, a Data Quality Report (DQR) should be issued. A method to automatically search the MDS and issue DQR's when rain gauge testing is performed is being considered by SMOS.
Calibration and Maintenance
Calibration Theory
The SMOSs are not calibrated as systems. The sensors and the data logger (which includes the analog-to-digital converter) are calibrated separately. All systems are installed using components that have a current calibration. The sensor calibrations are checked every six months in the field by SGP site operations personnel by comparison to calibrated references. Any sensor that fails a field check is returned to the manufacturer for recalibration. The Wind Monitors are returned to the manufacturer for recalibration after two years of use per manufacturer suggestion and given adequate funding. Therefore, it is possible that in some years the wind monitors are not sent back to the manufacturer for the 2 year recalibration and preventative maintenance. Overall, this should not lead to a problem, as the sensors rarely go out of calibration and are checked every 6 months.
Wind speed calibration is checked by rotating the propellor shaft at a series of fixed rpm's using an R. M. Young Model 18810 Anemometer Drive. The reported wind speeds are compared to a table of expected values and tolerances. If the reported wind speeds are outside the tolerances for any rate of rotation, the sensor is replaced by one with a current calibration.
Wind direction calibration is checked by using a vane angle fixture, R. M. Young Model 18212, to position the vane at a series of angles. The reported wind directions are compared to the expected values. If any direction is in error by more than 5 degrees, the sensor is replaced by one with a current calibration.
Air temperature and relative humidity calibrations are checked by comparison with a reference Vaisala Model HMI31 Digital Relative Humidity and Temperature Meter and HMP35 Probe. If the reported temperature and relative humidity vary by more than the sensor uncertainty from the reference, the probe is replaced by one with a current calibration.
Barometric pressure calibration is checked by comparison with a reference Vaisala PA-11 Barometer. If the reported pressure varies by more than the sensor uncertainty from the reference, the sensor is replaced by one with a current calibration.
Precipitation calibration is checked by allowing 500 ml of water to slowly pass through the sensor. If the reported number of tips varies by more than one from the expected value, the rain gauge is replaced by one with a current calibration.
The ARM SMOS web site contains a complete calibration History, as well as information on instrumentation, data collection and processing ( ARM, 2005). General information on ARM data quality (ARM, 2003b) can be found as well. Or see the ARM Program homepage (ARM, 2003a).
For information on the calculation of parameters derived by UCAR/JOSS from
the raw parameters available, see Section 2.2.
These data contain one-minute resolution surface meteorological data from the
Atmospheric Boundary Layer Experiments (ABLE) operated by the Argonne National
Laboratory in the Walnut River Watershed in Butler County Kansas (east of
Wichita). ABLE is a research initiative devoted to atmospheric research.
This location is within the existing boundaries of DOE's Atmospheric
Radiation Measurement (ARM) Southern Great Plains (SGP) Clouds and Radiation
Testbed (CART) site. The ABLE Automated Weather Station (AWS) Network consists
of five stations.
Instrumentation
The AWS stations directly measure:
Wind speed at 10 m, Precision: 0.01 m/s; Uncertainty: +/-1% for
2.5 to 30 m/s, increases to +/-0.5 m/s when 0.5 m/s is reported.
Propellor anemometer and wind vane, R. M. Young Model 05103 Wind Monitor
Wind direction at 10 m, Precision: 0.1 deg; Uncertainty: +/-5 deg
Air temperature at 2 m, Precision: 0.01 C; Uncertainty: +/-0.7 C
(This will eventually improve when an aspirated reference is obtained.)
Thermistor and Vaisala RH, Campbell Scientific Model HMP35C Temperature and
Relative Humidity Probe
Relative humidity at 2 m, Precision: 0.1% RH; Uncertainty: +/-2.06% RH
(0% to 90% RH), +/-3.04% RH (90% to 100% RH)
Thermistor and Vaisala RH, Campbell Scientific Model HMP35C Temperature and
Relative Humidity Probe
Barometric pressure at 1 m, Precision: 0.01 kPa; Uncertainty: +/-0.035 kPa
Digital barometer, Vaisala Model PTB201A
Precipitation, Precision: 0.254 mm; Uncertainty: +/-0.254 mm (unknown
during strong winds and for snow)
Electrically heated, tipping bucket precipitation gauge, MetOne Model 385
Rain/Snow Gage
The data logger is a Campbell Scientific Model CR10X-1M Measurement &
Control Module with 1 MByte memory; Precision: A function of input type
and range, Uncertainty: 0.2% of Full Scale Range for Analog Inputs
Topo maps and aerial photos are available at:
http://gonzalo.er.anl.gov/ABLE/sitelatlon.html
(ANL, 2004b).
Data Collection and Processing
The AWS sensors are mounted on a 10 meter, triangular tower,
except for the rain gauge.
The wind monitor propeller anemometer produces a magnetically
controlled AC output whose frequency is proportional to the wind speed.
The Wind Monitor direction vane drives a potentiometer, which is part
of a resistance bridge. The Wind Monitor is mounted on a cross-arm
at a height of 10 m.
The T-RH probe temperature sensor, a thermistor, is connected into a
resistance bridge. The Vaisala RH circuitry produces a voltage that is
proportional to the capacitance of a water vapor absorbing, thin polymer
film. The T-RH probe is mounted in an R. M. Young Mode l43408 Gill
Aspirated Radiation Shield. The Radiation Shield is mounted at a height
of 2 m on the southern face of the tower.
The barometric pressure sensor uses a silicon capacitive pressure
sensor and is housed in a weatherproof enclosure along with a data logger,
a storage module, and serial communications equipment, all mounted on the
tower at a height of 1.5 m.
The rain-snow gauge has a 12-inch orifice and is located near the
tower. A thermostatically controlled heater melts frozen precipitation. The
water is funneled to a tipping bucket, which triggers a magnetic reed
switch. An Alter Shield is used to increase the reliability of rain
collection in high winds and of snow collection.
The data logger measures each input once per second except for
barometric pressure, which is measured once per minute. The data
logger produces one- and 30-minute averages of wind speed, vector-averaged
wind direction, air temperature, and relative humidity.
The one-minute output includes the barometric pressure reading and total
precipitation during the minute. The 30-min output includes
30-min-total precipitation, average air temperature, average relative
humidity, and barometric pressure.
More information on ABLE AWS can be found on the
ABLE Home Page (
ANL, 2004a).
For information on the calculation of parameters derived by UCAR/JOSS from
the raw parameters available, see Section 2.2.
The Iowa Environmental Mesonet (IEM) Automated Weather Observing System (AWOS)
is a suite of sensors, which
measure, collect and disseminate weather data to help meteorologists, pilots
and flight dispatchers prepare and monitor weather forecasts, plan flight
routes, and provide necessary information for correct takeoffs and landings.
The sensors measure weather parameters such as wind speed and direction,
temperature and dew point, visibility, cloud heights and types, precipitation,
and barometric pressure. AWOSs are categorized as either Federal or NonFederal.
Federal AWOSs were purchased and are currently maintained by the FAA. NonFederal
AWOSs are purchased and maintainted by state, local, and private organizations.
The AWOS stations in this composite are operated by the Iowa Department of
Transportation and distributed by the IEM.
There are 35 AWOS stations in this BAMEX 2003 1-minute Surface Composite.
All data contained in this composite dataset were collected on stations
manufactured by Artais of Columbus, OH, a division of Vaisala.
The following are descriptions of the AWOS station data.
Further details can be found in the AWOS Operations Manual
(USDOT, 1988).
Temperature/Dewpoint
AWOS measure Temperature and Dewpoint at 1-min intervals. When the dew
point sensor is recalibrated, a large jump in dew point can occur. See the
report about
Iowa
AWOS calibration issues (Herzmann, 2004)
for a complete description.
Station Pressure and Derived Pressure Elements
AWOS takes 10-sec measurements from at least two independent
pressure sensors and computes respective 1-min averages. A minimum of
5 measurements are required to compute a 1-min average. The 1-min
averages from each sensor are compared to verify that differences do not
exceed 0.04" Hg. If the sensors are in agreement, the lowest pressure
reading from all sensors is reported. If the sensor differences exceed
0.04" Hg, the data are reported as "missing". The reported pressure is
then used by AWOS in the computation of derived parameters (e.g.,
altimeter reading). UCAR/JOSS takes the altimeter reading and converts it back
to station pressure using the algorithms found in the
Smithsonian Meteorological Tables. Sea Level Pressure is then calculated
from station pressure using standard
GEMPAK algorithms
(Unidata, 2003).
Wind
AWOS measures wind speed and direction at 1-sec intervals. Algorithms to
produce 1-minute data are not currently available. Gust Speed was set to
missing by UCAR/JOSS if the value was 0.
Precipitation
AWOS measures precipitation and 1-min intervals and reports cumulative
precipitation each minute. The cumulative precipitation value is reset
at 55 minutes after each hour. JOSS computes 1-minute precipitation values
by taking the difference of two consecutive cumulative 1-min precipitation
values. If this difference is negative at any point during the hour, then
that minute is treated as a reset as well. The precipitation reported at each
minute by UCAR/JOSS is the precipitation that fell during the previous minute.
Cloud cover
Iowa AWOS ceiling/cloud codes were mapped to the QCF ceiling height and cloud
codes. The web page the contains the Iowa AWOS code definitions is:
http://mesonet.agron.iastate.edu/AWOS/skyc.phtml.
The USDOT FAA AWOS
Data Acquisition System (ADAS)/AWOS Interface Control Document
(USDOT, 1998) contains
detailed technical documentation.
For more information see the Iowa Environmental Mesonet AWOS Network website
( IEM, 2004a) or the
.
FAA Automated Weather Observing System Information
website (FAA, 2004).
As the name implies, these automated weather stations are located at schools
throughout the state.
Currently, KCCI-TV
(Des Moines, IA) and KELO-TV
(Sioux
Falls, SD) have graciously provided the IEM with the ability to process data
from their observing networks. IEM is pursuing other TV stations, for their
networks as well. There are 65 Iowa School Network stations included in this
BAMEX 2003 1-minute surface composite.
Many of the school net stations are not located in good meteorological
locations. While the stations may be accurate, their data may not be
representative of the area in general. Often, they are placed on top of
buildings and may have obstructions which could skew wind and temperature
readings. The stations are placed at schools for educational purposes and to
get students interested in the weather.
Descriptions of the instrumentation, siting, and algorithms used by the school
networks to collect this data are not currently available.
Pressure, dewpoint and calculated sea level pressure were calculated by
UCAR/JOSS. For information on the calculation of parameters derived by
UCAR/JOSS from the raw parameters available, see
Section 2.2. For the purpose of these calculations, relative humidity
values between 0 and 10 were considered bad, temperatures >= 130 were ignored,
and altimeter values > 1000 were ignored. Station pressures that did not fall
between 300 and 1200 mb, and calculated sea level pressures that did not fall
between 800 and 1200 mb were flagged bad.
The IEM school network measures precipitation at 1-minute intervals and reports
cumulative precipitation each minute. The cumulative precipitation value is
reset at the beginning of every month. 1-minute precipitation values
were determined by taking the difference between consecutive records.
Precipitation reported at each minute is the precipitation that fell during the
previous minute.
More information on this network can be found on the
IEM School Network webpage (IEM, 2004b).
The Louisiana Agriclimatic Information System (LAIS) is a network of 24
automated weather stations operated by the
LSU AgCenter
(LSU, 2004). The
network is managed by the
Department of Biological and Agricultural Engineering
(BAE, 2004).
Stations are located primarily at
farms of the Louisiana Agricultural Experiment Station, the research arm of
the Louisiana State University Agricultural Center. These automated stations
collect air temperature, soil temperature, humidity, rainfall, wind and
solar radiation observations. These data are regularly transmitted to a
centralized computer and are subsequently made available, via the internet,
to the public. Air temperature, rainfall and wind, as well as dew point
calculated by UCAR/JOSS from the LAIS humidity, are included in this
composite. There are 21 LAIS stations included in this BAMEX 2003 1-minute
surface composite.
Mission
The Louisiana Agriclimatic Information System (LAIS) collects, processes and
distributes detailed climatic data relevant to agricultural production,
natural resource management, environmental protection and public safety.
Equipment Descriptions
Dataloggers:
Each LAIS station is equipped with a model CR23X datalogger manufactured by
Campbell Scientific.
A datalogger is a specialized computer which accepts electronic signals
from various instruments, performs mathematical functions on the data, and
records summaries in internal memory at designated intervals.
Communication: Most stations transmit data to a centralized computer
every five minutes by using a combination of RAD brand short-haul modems,
buried communications cable, and a Lantronix UDS-10 network interface. Some
stations have radios substituted in place of the buried cable, and some
still use telephone modems. Where the network interface and the weather
station are not within the same local calling area, data is generally
transmitted only once per day.
Power: The dataloggers operate on 12 volts direct current.
In most cases, this is provided by an internal battery that is kept fully
charged by a 30-watt solar panel. In some cases, the internal
battery is kept charged by an adapter plugged into a regular 110-volt AC
outlet. Some stations substitute a larger gelcell battery for the internal
battery.
Air Temperature and Relative Humidity:
A dual sensor measures temperature and relative humidity. Each station has a
Vaisala HMP35A, which
has a platinum temperature sensing element, and a Humicap relative humidity
sensor.
Backup Air Temperature:All stations have a second temperature
sensor to help in judging the quality of the primary temperature sensor's
data. If both temperatures agree, it is unlikely that they are far off from
actual air temperature. In many cases, the backup sensor is identical to
that used in National Weather Service electronic Maximum Minimum Temperature
Systems. All stations will soon have the
Campbell Scientific
107 thermistor
as the backup, along with a matching sensor at a height of 9 meters. The
backup temperature is not included in this composite.
Wind Speed and Direction: All stations measure both wind speed and
direction with an RM Young
Wind Monitor, configured for use with
Campbell Scientific dataloggers, at a height of 10 meters.
Precipitation: All stations have
Handar 444A tipping bucket rain gauge or a similar unit manufactured by
Hydrological Services. Either brand transmits a signal to the datalogger
each time .01 inches of rainfall accumulates. Many of the stations also
have an official manual precipitation gauge in the same location. The
tipping bucket rain gauge reports accumulated rainfall in inches since
midnight CST. UCAR/JOSS calculates 1-minute precipitation in UTC from the
accumulated precipitation. Precipitation reported in this composite is the
precipitation that fell during the previous minute.
Barometric Pressure:
All stations in the LAIS network also observe barometric pressure.
Each station consists of a datalogger that observes several electronic
instruments on a 3-second interval. Output is generated by the datalogger
every 3 seconds, although this data is normally not archived, every minute,
hourly, daily at midnight, and daily at 7am. Only the 1-minute data is
included in this composite.
Dewpoint and calculated sea level pressure were calculated by UCAR/JOSS.
For information on the calculation of parameters derived by UCAR/JOSS from
the raw parameters available, see Section 2.2.
During the BAMEX time period, the LAIS instrumentation was not
routinely calibrated or maintained so some stations have problems
with certain parameters (particularly pressure and dew point).
After the BAMEX period the LAIS stations have started to be routinely
calibrated and maintained.
More information on this network can be found on the
LAIS
webpage (LAIS, 2004).
The BAMEX 2003 One Minute Surface Composite observation data
contains ten metadata parameters and 38 data parameters and flags. The
metadata parameters describe the station location and time at which the
data were collected. The time of observation is reported both in Universal
Time Coordinated (UTC) Nominal and UTC actual time. For this one minute
surface composite, reported nominal time and actual time are the same.
Days begin at UTC 0001 and end at UTC 0000 the following day. The table
below details the data parameters in each record. Several data parameters
have an associated Quality Control (QC) Flag Code which are assigned by the
Joint Office for Science Support (JOSS). For a list of possible QC Flag
values see the Quality Control Section 3.0.
This dataset contains only one minute observations for the BAMEX 2003
domain and time period. The component datasets from which this dataset was
compiled are available on-line in native format via the
BAMEX 2003 Master
Table of Datasets (UCAR/JOSS, 2003)
When not present in the raw data, station pressure is computed from altimeter
using the algorithms found in the Smithsonian
Meteorological Tables (1949).
Calculated Sea Level pressure is computed from station pressure,
temperature, dewpoint, and station elevation using the formula of
Wallace and Hobbs (1977).
When not present in the raw data, the dewpoint temperature was
computed by UCAR/JOSS from station pressure, temperature, and relative
humidity (RH) using the formula from Bolton (1980)
. For the purpose of this calculation, RH <= 104.0 was considered
valid. For RH > 104.0, the dew point was set to missing. Dew point was
calculated for the following networks: ARM SMOS, ABLE AWS, Iowa School Net,
and LAIS.
The BAMEX 2003 One Minute Surface Composite was formed
from several datasets:
During the JOSS Horizontal Quality Control (JOSS HQC) processing,
station observations of pressure, temperature, dew point, wind speed and
wind direction were compared to "expected values" computed using an
objective analysis method adapted from that developed by
Cressman (1959) and
Barnes (1964). The JOSS HQC method allowed for short term (>/= 30 day)
variations by using 30 day standard deviations computed for each parameter
when determining the acceptable limits for "good", "questionable", or
"unlikely" flags.
"Expected values" were computed from inverse distance
weighted station observations within a 200 km Radius Of Influence (ROI)
centered about the station being quality controlled (the station being
quality controlled was excluded); i.e.;
theta_e = < theta(i)/w(i) > / < w(i) >
Where theta_e is the "expected value" of the parameter at the site in
question, theta(i) is the observed value of the parameter at site i, w(i)
is the weighting factor for site i (here the inverse of the distance
between site i and the station being quality controlled), and <...> is
the sum over all stations "i" in the current ROI that have valid
observations of the parameter at the time in question.
Data were always compared at like solar times.
To determine an observation's HQC flag setting, the difference between
the actual observation and its "expected value" was compared to that
parameter's normalized standard deviation. Normalizing factors (also
called the sensitivity coefficients) were chosen to control the "good",
"questionable", and "unlikely" flag limits for each parameter. See
Table 3-1 for BAMEX 2003 normalizing factors.
Table 3-2 contains the HQC flag limit ranges
derived from the normalizing factors given in
Table 3-1 and estimated standard deviations for each parameter
so that 95% of the QC limits applied to the BAMEX 2003 data
fell within these ranges. For example, 95% of the observed station
pressure values that were flagged as "good" were within 1.1 mb of the
expected value. The significant overlap of the ranges seen in
Table 3-2 was partially due to seasonal and station
differences in
standard deviations. The actual HQC limits applied at any particular
time depended upon the dynamic nature of the particular station's
parameter values over time.
Data were never changed, only flagged.
HQC was only applied to station pressure, calculated sea level pressure,
temperature, dew point, wind speed and wind direction.
If the calculated sea level pressure quality control
information was available, its flag was applied to the station and
sea level pressures. If the calculated sea level pressure could not
be quality controlled, the sea level pressure quality control flag
was applied to the station pressure. If the sea level pressure could
not be quality controlled, the station pressure quality control flag
was not overridden. Note that there were no sea level pressures in this
composite.
Table 3-1 Normalizing factors used for BAMEX 2002 One Minute
Surface Composite
The squall/gust wind speed data were not quality controlled.
General consistency checks were also applied to the dry bulb
temperature, wind direction, and the relationship between precipitation and
cloud amount/cloud cover. If the dew point temperature was greater than the
dry bulb temperature both values were coded "questionable". Also, wind
direction for observed "calm" winds was given the same QC code as the wind
speed. If precipitation was reported, but the cloud amount was "none" or
"clear", then both the cloud amount and precipitation values were coded
"questionable".
Several impossible values were also checked. Negative wind speeds
were coded "unlikely". Negative squall/gust wind speeds were coded
"unlikely". Wind directions of less than 0 degrees or greater than 360
degrees were coded "unlikely". If these consistency checks would have
upgraded the quality control flags previously set by HQC or gross limit
checks, then they were not applied. However, if these consistency checks
would have degraded the previously set QC flags, they were applied.
The JOSS HQC scheme relied on spatial and temporal continuity to
flag the data. It has been shown that this method works very well for
temperature, dew point, pressure, and wind speed, but is not a very good
scheme for the wind direction. The flags appear to be overly lax and
perhaps could be tightened.
Gross limit checks were also used to determine the quality of the
precipitation values. The gross limits are shown in
Table 3-3. Certain
"questionable" and "unlikely" data values were also manually inspected.
After inspection, the quality control flag may have been manually modified
to better reflect the physical reasonableness of the data. Data were never
modified, only flagged. Negative precipitation was also coded "unlikely".
See Table 3-4 for a list of the possible quality
control flags and their
meanings.
Table 3-3 - Precipitation Gross Limit Values
Argonne National Laboratory, cited 2004a: ABLE Automatic Weather Station
(AWS) [Available online from
http://www.atmos.anl.gov/ABLE/aws.html]
Argonne National Laboratory, cited 2004b: ABLE Site Latitude/Longitude
[Available online from:
http://gonzalo.er.anl.gov/ABLE/sitelatlon.html]
ARM, cited 2003a: Atmospheric Radiation Measurement Program [Available
online from
http://www.arm.gov/]
ARM, cited 2003b: Data Quality HandS Explorer [Available online from
http://dq.arm.gov/cgi-bin/dqmenu.pl]
ARM, cited 2005: Surface Meteorological Observation System Instruments
for SGP (SMOS)[Available
online from http://www.arm.gov/instruments/instrument.php?id=36]
ARM, cited 2004d: SGP Overview Map [Available online from
http://www.arm.gov/sites/sgp/maps.stm]
ASOS User's Guide, 1998, ASOS Project Office, NOAA, National Weather
Service, Washington D.C., June 1998. [Available online from
http://www.nws.noaa.gov/asos/aum-toc.pdf]
ASOS User's Guide Appendices, 1998, ASOS Project Office, NOAA, National
Weather Service, Washington D.C., June 1998. [Available online from
http://www.nws.noaa.gov/asos/appen.pdf]
BAE, cited 2004: Department of Biological and Agricultural Engineering
[Available online from
http://www.bae.lsu.edu]
Barnes, S. L., 1964: A technique for maximizing details in numerical
weather map analysis. J. Appl. Meteor., 3, 396-409.
Bolton, D., 1980: The computation of equivalent potential temperature.,
Mon. Wea. Rev., 108, pp 1046-1053.
Cressman, G. P., 1959: An operational objective analysis system.
Mon. Wea. Rev., 87, 367-374.
FAA, cited 2004: Automated Surface Observing System [Available online
from
http://www.faa.gov/asos/asosinfo.htm]
FAA, cited 2004b: Automated Weather Observing System [Available online
from
http://www.faa.gov/asos/awosinfo.htm]
Herzmann, 2004: About the Iowa AWOS calibration issues, 25 January 2004
[Available online from
http://mesonet.agron.iastate.edu/AWOS/reports/awos040125.pdf]
IEM, cited 2004a: Iowa Environmental Mesonet AWOS Network [Available
online from
http://mesonet.agron.iastate.edu/AWOS]
IEM, cited 2004b: Iowa Environmental Mesonet School Network [Available
online from http://mesonet.agron.iastate.edu/schoolnet]
LAIS, cited 2004: Louisiana Agriclimatic Information [Available online
from
http://www.agctr.lsu.edu/weather/]
LSU, cited 2004: LSU AgCenter [Available online from
http://www.lsuagcenter.com]
NWS, cited 2003: Automated Surface Observing System [Available online
from
http://www.nws.noaa.gov/asos]
Smithsonian Meteorological Tables, Table No. 65, p.269. Smithsonian
Institution Press, Washington, D.C., September, 1949.
UCAR/JOSS, cited 2003: BAMEX Master Table of Datasets [ Available online
from
http://www.joss.ucar.edu/bamex/dm/archive/index.html]
Unidata, cited 2003: GEMPAK/N-AWIPS [Available online from
http://www.unidata.ucar.edu/packages/gempak]
United States Department of Transportation (USDOT), 1988. AWOS
Operations Manual, Federal Aviation Administration.
USDOT, 1998: U.S. Department of Transportation, Federal Aviation
Administration Interface Control Document between AWOS Data Acquisition System
(ADAS) and Automated Weather Observing System (AWOS), April 14, 1998
[Available online from http://mesonet.agron.iastate.edu/AWOS/manual/]
Wallace, J.M., P.V. Hobbs, 1977: Atmospheric Science, Academic Press,
467 pp.
World Meteorological Organization (WMO), 1988: Manual on Codes
Volume I, Part B - Binary Codes. WMO, Geneva, Switzerland.
2.0.3 DOE ABLE AWS Algorithms
2.0.4 Iowa Environmental Mesonet (IEM) Automated Weather Observing System (AWOS) Algorithms
IA Code Description QCF Ceiling Code QCF Cloud Code
0 No report 15 15
1 Scattered (10-50% Coverage) 4 11
2 Broken (60-90% Coverage) 4 12
4 Overcast (90+% Coverage) 4 8
8 Full Obscuration 5 9
17 Partial Obscuration (scattered) 4 10
18 Partial Obscuration (broken) 4 10
20 Partial Obscuration (overcast) 4 10
32 Indefinite 5 15
64 Clear (No clouds under 12000 ft) 2 0
128 Few (<10% coverage) 4 1
255 Missing 15 15
* Unknown Code error error
2.0.5 Iowa Environmental Mesonet (IEM) School Network Algorithms
2.0.6 Louisiana Agriclimatic Information System (LAIS) Algorithms
2.1 Detailed Format Description
Parameters Units
---------- -----
Date of Observation UTC Nominal
Time of Observation UTC Nominal
Date of Observation UTC Actual
Time of Observation UTC Actual
Network Identifier Abbreviation of platform name
Station Identifier Network Dependent
Latitude Decimal degrees, South is negative
Longitude Decimal degrees, West is negative
Station Occurrence Unitless
Station Elevation Meters
Station Pressure, QC flag Hectopascals (mb)
Reported Sea Level Pressure, QC flag Hectopascals (mb)
Computed Sea Level Pressure, QC flag Hectopascals (mb)
Dry Bulb Temperature, QC flag Celsius
Dew Point, QC flag Celsius
Wind Speed, QC flag m/s
Wind Direction, QC flag Degrees
Total Precipitation, QC flag mm
Squall/Gust Indicator Code Value
Squall/Gust Value, QC flag m/s
Present Weather, QC flag Code Value
Visibility, QC flag Meters
Ceiling Height (first layer) Hundreds of feet
Ceiling Flag (first layer), QC flag Code Value
Cloud Amount (first layer), QC flag Code Value
Ceiling Height (second layer) Hundreds of feet
Ceiling Flag (second layer), QC flag Code Value
Cloud Amount (second layer), QC flag Code Value
Ceiling Height (third layer) Hundreds of feet
Ceiling Flag (third layer), QC flag Code Value
Cloud Amount (third layer), QC flag Code Value
The list of code values for the Present Weather is too large to reproduce
in this document. Refer to WMO, 1988 for a complete
list of Present Weather codes.
The code values for the Squall/Gust Indicator are:
Code Definition
---- ----------
blank No Squall or Gust
S Squall
G Gust
The code values for the ceiling flag Indicator are:
Code Definition
---- ----------
0 None
1 Thin
2 Clear below 12,000 feet
3 Estimated
4 Measured
5 Indefinite
6 Balloon
7 Aircraft
8 Measured/Variable
9 Clear below 6,000 feet (AUTOB)
10 Estimated / Variable
11 Indefinite / Variable
12 12-14 reserved
15 Missing
The code values for the Cloud Amount Indicator are:
Code Definition
---- ----------
0 0 ( or clear)
1 1 okta or less, but not zero or 1/10 or less, but not zero
2 2 oktas or 2/10-3/10
3 3 oktas or 4/10
4 4 oktas or 5/10
5 5 oktas or 6/10
6 6 oktas or 7/10-8/10
7 7 oktas or more, but no 8 oktas or 9/10 or more, but not 10/10
8 8 oktas or 10/10 (or overcast)
9 Sky obscured by fog and/or other meteorological phenomena
10 Sky partially obscured by fog and/or other meteorological
phenomena
11 Scattered
12 Broken
13 13-14 Reserved
15 Cloud cover is indiscernible for reasons other than fog or
other meteorological phenomena, or observation is not made.
2.2 Data Remarks
3.0 Quality Control Processing
These BAMEX 2003 One Minute Surface Composite datasets
were collected over the BAMEX 2003 domain (i.e., 30N to 48N latitude and
80W to 104W longitude) and time period (20 May 2003 through 6 July 2003)
and were combined to form a surface composite. The composite was quality
controlled to form the final BAMEX 2003 One Minute Surface Composite.
Parameter Good Questionable Unlikely
--------- ---- ------------ --------
Station Pressure 0.2 0.2 0.5
Calculated SLP 0.4 0.4 1.0
Dry Bulb Temperature 0.5 0.5 1.0
Dew Point Temperature 0.5 0.5 1.0
Wind Speed 2.25 2.25 4.0
Wind Direction 1.22 1.22 2.2
Table 3-2 Ranges of HQC flag limit values for BAMEX 2003
One Minute Surface Composite
Parameter Good Questionable Unlikely
--------- ---- ------------ --------
Station Pressure (mb) < 1.1 [0.5-2.8] > 1.1
Calculated SLP (mb) < 2.5 [0.9-6.2] > 2.2
Dry Bulb Temperature (deg.C) < 2.6 [0.9-5.2] > 1.7
Dew Point Temperature (deg.C) < 2.7 [0.7-5.4] > 1.4
Wind Speed (m/s) < 6.1 [1.6-10.8] > 2.8
Wind Direction(degrees) < 156.7 [79.5-180.0] >143.4
Parameter Good Questionable Unlikely
--------- ---- ------------ --------
1 Minute Precip < 3.0 mm >= 3.0 mm >= 6.0 mm
Table 3-4 - Quality Control Flags
QC Code Description
------- -----------
U Unchecked
G Good
M Normally recorded but missing.
D Questionable
B Unlikely
N Not available or Not observed
X Glitch
E Estimated
C Reported value exceeds output format field size or
was negative precipitation.
T Trace precipitation amount recorded
I Derived parameter can not be computed due to
insufficient data.
4.0 References