BAMEX 2003 Hourly Surface Composite

1.0 General Description

This dataset contains hourly 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:

The Hourly Surface data extract from the 1-minute contains DOE Atmospheric Boundary Layer Experiments (ABLE) Automated Weather Station (AWS) data only. More information on ABLE AWS can be found on the ABLE Home Page (ANL, 2004).

Data for the Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) 2003 domain (30N to 48N latitude and 80W to 104W longitude) and time period (20 May 2003 through 6 July 2003) are contained within this dataset. This BAMEX 2003 Hourly Surface Composite dataset contains data from 2419 stations.

Section 2.0 contains a detailed description of the instrumentation, siting, and algorithms used by the source network to collect the data. Section 2.1 contains a detailed description of the format of the composite dataset. Please review Section 2.2 for information on data processing, and for specific issues that affect the data. See Section 3.0 below for the quality control processing performed by UCAR/JOSS on this dataset. Section 4.0 contains references.

2.0 Detailed Data Description

2.0.1 Department Of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Surface Meteorological Observation System (SMOS) [ARMSFC] Surface Meteorological Data Algorithms

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 stations included within this BAMEX 2003 Hourly Surface Composite.

The ARM SMOS website 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).

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 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

Assessment of System Uncertainties for Primary Quantities Measured

Uncertainty is the range of probable maximum deviation of a measured value from the true value within 95% confidence limits. It is defined as the square root of the sum of all random errors squared plus the square root of the sum of all bias errors squared. The errors are assumed to be statistically independent.

All SMOS uncertainty analyses are based on manufacturer's specifications. Manufacturers specify accuracies in several ways. Some give absolute range of error, some give uncertainties as defined above, while others give rms errors. In this analysis, rms errors are multiplied by 2. This results in confidence limits of approximately 95%.

Data Acquisition Errors

The Campbell Scientific CR10 A/D converter accuracy is +/-0.2 % of full scale range. The time base accuracy is +/-1 minute per month, or about 23 ppm. The Site Data System checks the time-of-day clock once per day and corrects the SMOS clock if it is off by more than a minute.

Wind Speed

The NIST calibration uncertainty is specified as +/-1% for wind speeds from the sensor threshold to 30 m/s. The conversion error is negligible. The schedule of routine maintenance and sensor verification is designed to eliminate any long-term stability error.

The sensor threshold is specified as 1 m/s. The following estimates of the range of underestimation caused by the threshold assume a normal distribution of wind speeds about the mean. When the true wind speed is 1.0 m/s, the winds will be below the threshold 50% of the time. This will result in an underestimate of 0.5 m/s. When the true wind speed is 1.5 m/s, assuming the standard deviation will be between 0.25 and 1.00 m/s, the winds will be below the threshold between 2 and 31% of the time. This will result in an underestimate between 0.02 and 0.23 m/s. When the true wind speed is 2.0 m/s with a range of standard deviations between 0.25 and 1.00 m/s, the winds will be below the threshold between 0 and 16% of the time. This will result in an underestimate between 0 and 0.12 m/s.

If the reported wind speed is 0.5 m/s, an underestimate of 0.5 is probable. This would bias the measurement by -0.5. If the reported wind speed is 1.0 m/s, an underestimate of 0.19 to 0.30 m/s is possible. If the reported wind speed is 1.5 m/s, an underestimate of 0.02 to 0.20 m/s is possible. If the reported wind speed is 2.0 m/s, an underestimate of 0 to 0.10 m/s is possible.

The uncertainty range with 95% confidence is approximately:

+/- 1%for a reported wind speed from 2.5 to 30.0 m/s
-0.12 to +0.02 m/sfor a reported wind speed of 2.0 m/s
-0.22 to +0.00 m/sfor a reported wind speed of 1.5 m/s
-0.31 to -0.20 m/sfor a reported wind speed of 1.0 m/s
-0.51 to -0.49 m/sfor 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 Cwhen the wind speed is 6 m/s or greater
+/-0.89 Cwhen the wind speed is 3 m/s
+/-1.46 Cwhen 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 are 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.

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.

UCAR/JOSS derives hourly data from the 1-minute data provided by the source. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

2.0.2 Colorado Agricultural Meteorological Network (COAGMET)

The Colorado Agricultural Meteorological Network (COAGMET) consists of automated weather stations in Colorado operated by the Colorado Climate Center. For more information on COAGMET visit the COAGMET HomePage ( CSU, 2004). The information on COAGMET contained in this documentation was taken from this website. There are 15 COAGMET stations in this BAMEX 2003 Hourly Surface Composite.

Below is the description of a typical COAGMET station. Most stations have a similar configuration but sensors, dataloggers and siting vary somewhat throughout the network. Only the temperature, relative humidity, wind speed, wind direction and precipitation values are used to create this composite dataset, but the description of the sensor for every parameter is included here for reference.

Temperature, wind speed and wind direction values are averaged over the hour ending with the measurement time. Dewpoint temperature is calculated by UCAR/JOSS using the formula from Bolton (1980) and the temperature and relative humidity values from each station.

Temperature and Relative Humidity 

     * Model: Vaisala HMP35C Probe
     * Sensor Height: 1.5 meters
     * Temperature Specs
          o Temperature Measurement Range: -35 to 50 DegC
          o Thermistor Interchangeability Error: Typically <+-0.2 DegC over 0
            DegC to 60 DegC; +-0.4 DegC at -35 DegC
          o Polynomial Linearization Error: <+-0.5 DegC over -35 DegC to 50
            DegC
     * Relative Humidity Specs
          o RH Measurement Range: 0% to 100%
          o RH Accuracy (at 20 DegC) +- 2%, 0% - 90%; +-3% >90%
          o Temperature Dependence of RH Measurement: +-0.04% RH/DegC

Wind 

 
     * Model: R.M. Young 05103 Wind Monitor
     * Sensor Height: 2 meters
     * Wind Speed Specs
          o Range: 0-60 m/s
          o Starting Threshold: 1.0 m/s
          o Distance Constant (63% recovery): 2.7 m.
     * Wind Direction Specs
          o Range: 0-360 Deg. (355-360 open)
          o Starting Threshold 10 deg displacement: 0.9 m/s
          o Starting Threshold 5 deg displacement: 1.3 m/s

Precipitation 

     * Model: TE525 tipping bucket raingage
     * Specs
          o Sensor height >1m
          o Collector diameter - 154mm
          o 0.254mm/tip
          o accuracy +- 1% for precip of 50mm/hr or less
          o Operating temperature 0 to 50C (not accurate during winter)

Solar Radiation 

     * Model: Licor 200S Pyranometer
     * Specs
          o Sensor Height ~2m
          o 0-10 mv output range
          o Sensitivity typically 80 microamp/1000 W/m2
          o Linearity Maximum deviation 1% up to 3000 W/m2
          o Spectral response from 0.4 to 1.1 mu
          o Typical error under natural daylight +-3%, maximum +-5%

Soil Temperature 

     * Model: CSI Model 107 Soil Temp Probe (thermistor)
     * Specs
          o +- 0.4C for -33 to +48C all errors inclusive
          o Sensor depth 50mm and 150mm where two sensors used, 100mm where
            only one.

Leaf Wetness Sensor 

     * Model: CSI Model 237 - Circuit board with interlocking gold plated
       copper fingers, coated with flat latex paint to spread water layer.
       Measures electrical resistivity of water film.
     * Specs
          o Sensor height ~0.5m

Data Logger

  • Model: Campbell Scientific CR10

    Site Pictures

  • A picture of a CR10 installation at Burlington (brl02) can be found at: http://ccc.atmos.colostate.edu/~coag/ws02.gif. There is also a map of the COAGMET stations. ( CSU, 2004)

    2.0.3 National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) Algorithms

    This BAMEX 2003 Hourly Surface Composite contains data from 7 stations within the Great Lakes Environmental Research Laboratory (GLERL) network. The data was collected at 6 real-time meteorological stations at exposed coastal sites around southern Lake Michigan, and the Alpena station on Lake Huron.

    For more information on GLERL visit the GLERL website ( GLERL, 2004). The information on GLERL contained in this documentation was taken from this website. The GLERL website contains a map of the GLERL stations. By clicking on a station you can get to more detailed station information. The link "MetaData File" provides a description of the instrumentation at that station. Instrumentation varies somewhat by station. A typical installation contains an R.M. Young model 5103 Wind monitor, a CSI model 107 thermistor mounted in a naturally aspirated gill type radiation shield, and a CSI model CR10X. This units samples the sensors every 5 seconds and is set to an averaging interval of 5 minutes. The system is run from a 12A/hr gel cell battery which is charged from the AC line. Sensors are located 40-80 feet above the water.

    The GLERL stations report 5-minute frequency data. UCAR/JOSS converts these data to hourly. The remaining records are included in the BAMEX 2003 Mesonet Surface Miscellaneous Composite. Dew point and sea level pressure were calculated by UCAR/JOSS when possible. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    2.0.4 High Plains Climate Network (HPCN)

    The HPCN is developed by the High Plains Regional Climate Center (HPRCC) and includes data from a number of agricultural networks operated by various state agencies in the High Plains region. There are 112 HPCN stations in this BAMEX 2003 Hourly Surface Composite.

    Instrumentation 

    Sensor              Variable         Installation Ht. Accuracy 
---------------------------------------------------------------------------
Thermistor          Air Temperature          1.5 m      0.25 C 
Cup Anemometer      Wind Speed                 3 m    5% (0.5 m/s start-up) 
Wind Vane           Wind Direction             3 m      2 degrees 
Coated Circuit      Relative Humidity        1.5 m          5% 
Tipping Bucket      Precipitation       0.5 to 1 m          5%

    A pressure sensor has been added to some of the stations in the High Plains Climate Network, but not all. Relative humidity and temperature were used to calculate dewpoint (Bolton,1980). Sea level pressure was calculated from station pressure, when available. For information on the calculation of parameters derived by UCAR/JOSS, see Section 2.2.

    When present in the raw data, the following data quality flags determined by the source were translated to UCAR/JOSS quality control flags. Flag 'E' indicating that the values was estimated by the HPCC quality control program, based on distance weighting from surrounding stations, flag 'e' indicating that the HPCC quality control program is not confident of the estimate, and flag 'R' indicating that the value was estimated by the HPCC quality control program, based on weighted linear regression from surrounding stations, were translated to UCAR/JOSS Quality Control flag 'E'. Flag 'M' indicating missing data was translated to UCAR/JOSS Quality Control flag 'M', also indicating missing data. For a complete list of Quality Control flags possible in this UCAR/JOSS Hourly Surface Composite, see Table 3.4

    For more information see the HPCN Home Page (HPRCC, 2003).

    2.0.5 Illinois Air Monitoring Network (AIRQUAL_IL) Algorithms

    The Illinois air monitoring network is composed of instrumentation owned and operated by both the Illinois Environmental Protection Agency and by cooperating local agencies. Information on the algorithms used to collect the data are not available at this time. More information, including a map of station locations, can be found in the Illinois Annual Air Quality Report 2003( Illinois, 2003). There are 20 Illinois Air Quality stations included in this BAMEX 2003 Hourly Surface 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.

    2.0.6 Illinois State Water Survey (ISWS) Illinois Climate Network (ICN) Algorithms

    The Illinois Climate Network (ICN) consists of 19 automated weather stations in Illinois operated by the Illinois State Water Survey. These stations were installed between 1988 and 1991 and are located on the University of Illinois Agricultural Experiment Station Farms, the Southern Illinois University Agronomy Experiment Farms, and on various community college campuses around the state. Each station consists of a 10 meter tower equipped with weather instruments which are interrogated every 10 seconds by a datalogger which computes hourly averages and totals. These hourly values are then included by UCAR/JOSS in this BAMEX 2003 Hourly Surface Composite.

    Information regarding the ICN site instrumentation is given below. For detailed ICN site descriptions, ICN instrument verification, ICN Quality Control and more, refer to Hollinger, 1994. Also see the WARM Illinois Climate Network Data website.

    Wind Speed and Direction

    Wind speed and direction are monitored with an R.M. Young 8003 anemometer fitted with a wide range molded polypropylene plastic four-blade propeller. An anemometer is mounted on each tower at a height of 10 m. The anemometer has a functional wind speed range of 0 to 50 meters per second (m/s), with a threshold speed of 0.2 to 0.4 m/s. The propeller weighs 31 grams and has a distance constant of 3.3m. The distance constant is the wind passage required for a 63 percent recovery from a step change in wind speed. With wind speeds greater than 1.3 m/s, the propeller makes one revolution per 30 cm of wind passage. Below wind speeds of 1.3 m/s, slippage increases (i.e., a greater wind passage is needed per revolution) down to the wind threshold.

    Wind direction is measured from 0 to 355 degrees. The 10K-ohm precision resistor that measures wind direction has an open section in the potentiometer element from 355 to 360 degrees. The open section of the potentiometer element is oriented to the north represented by a direction signal of zero. Rotation of the vane clockwise from north to east, south, and west causes the azimuth signal to increase in value until the vane reaches 355 degrees, where the signal falls to zero. The vane and propeller combination has a damping ratio of 0.34.

    Air Temperature and Dew Point

    Air temperature and relative humidity are monitored using a Vaisala temperature and humidity probe, model HMP112Y. The temperature- humidity probe is mounted inside a radiation shield attached to a leg of each weather tower at a height of approximately 2 m. The operating temperature is from -5 to +55 degrees Celsius (C). A 216 micrometer sintered filter protects a platinum thermistor (the temperature sensor) and a capacitance film (the humidity sensor) from dust particles. The temperature measurement range is -40 to +80 degrees C with an output uncertainty of +/-0.3 degrees C at 20 degrees C. The measurement range for relative humidity is 0 to 100 percent. In the 0 to 80 percent range, output uncertainty is +/- 2 percent at +20 degrees C. The output uncertainty in the 80 to 100 percent range is +/-3 percent at 20 degrees C. UCAR/JOSS uses the reported relative humidity to compute the dew point (Bolton, 1980). The dew point is reported in this BAMEX 2003 Hourly Surface Composite.

    Precipitation

    A Belfort weighing bucket rain gage fitted with an 8-inch collector opening, evaporation funnel, and a potentiometer is used to measure precipitation at each site. Each rain gage is located outside the rain shadow area of the weather tower. The 203 mm (8-inch) collector allows each gage to accept up to 305 mm (12 inches) of precipitation. Although this capacity is expressed in inches, it is actually measured in terms of weight, with 25.4 mm (1 inch) of precipitation being equivalent to 902.6 g (29.02 ounces) of water at 17 degrees C (62.6 degrees F). The accuracy of this type of rain gage over the range 0 to 152.4 mm (0 to 6 inches) is 0.26 mm (0.03 inches; +/- 0.5 to 1 percent), and over the range 152.4 to 304.8 mm (6 to 12 inches) is 1.52 mm (0.06 inches; 1 percent). The evaporation funnel is removed from the rain gage collector during the winter and a one-quart charge of environmentally safe anti- freeze added to each rain gage bucket to help melt frozen precipitation and protect the bucket from damage due to the expansion of freezing water in the bucket.

    Precipitation is determined by ICN by subtracting the weight of water collected in a bucket at the end of an hour or day from the weight at the beginning of an hour or day. Negative hourly observations are assumed to be zero and are due to "noise" in the instrument caused by evaporation, wind eddies, pressure fluctuations, electrical noise, and mechanical backlash of the instrument. ICN is working to correct these problems.

    Barometric Pressure

    A Campbell Scientific SBP270 barometric pressure sensor with an accuracy of +/- 0.2 millibar (mb) over a pressure range of 800 to 1000mb is used to measure barometric pressure at each station. Operating temperature of the sensor is -18 to 79 degrees C. The barometer in the sensor is a Sentra Model 270 variable capacitance barometer.

    2.0.7 Iowa Environmental Mesonet (IEM) School Network (IA_SCH_NET) Algorithms

    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. There are 65 Iowa School Network stations included in this BAMEX 2003 Hourly Surface Composite. More information on this network can be found on the IEM School Network webpage (IEM, 2004).

    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 these data are not currently available.

    Pressure, dewpoint and calculated sea level pressure were calculated by UCAR/JOSS. IEM School Network reports accumulated precipitation. UCAR/JOSS reports hourly precipitation in this BAMEX 2003 Hourly Surface Composite by taking the difference between two hourly accumulated values. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    2.0.8 Kansas Ground Water Management District #5 (GWMD5) Network Algorithms

    The GWMD #5 network is located in south central Kansas. Data are collected using Campbell Scientific, Inc. MetData1 weather stations (Campbell Scientific, 2003). Station elevations were estimated by the GWMD5 from USGS topographic maps. There are 10 GWMD5 stations in this BAMEX 2003 Hourly Surface Composite.

    Dew point was calculated by UCAR/JOSS when possible. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    The algorithms used to produce the GWMD5 hourly surface data are not currently available.

    2.0.9 WK Kellogg Biological Station (KBS) Long-Term Ecological Site (LTER) Network (KELLOGG) Algorithms

    These data were provided by the W.K. Kellogg Biological Stations (KBS). The KBS LTER Home Page is at http://lter.kbs.msu.edu. This station is run by Michigan State University and is located in Hickory Corners, MI. There is one station in this network. KBS provided the following information about this station.

    Instrumentation Campbell Scientifc sensors are connected to a CR10x datalogger, which takes readings every 10 seconds and stores hourly integrated values. Temperature is measured by a Campbell Scientific model 107 temperature probe, housed in a vented shield. Wind speed is measured by a Met One model 014A, wind direction by Met One model 024A. The RH is measured with a Vaisala HMP45C. The pressure is measured with a Vaisala PTB101B barometer.

    Instruments to measure wind speed and direction are mounted on a tower at 10 m. A thermometer, and an RH probe (with a built-in thermometer) are mounted at about 3 m. Precipitation is measured with a Belfort model 5-780 weighing bucket rain gauge.

    Relative humidity has been downloaded by KBS directly from calibrated field instruments without post-collection quality checks. Use with caution.

    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.

    2.0.10 Kentucky Air Monitoring Network (AIRQUAL_KY) Algorithms

    The State of Kentucky has operated and air-quality monitoring network since July 1967. The locations of the monitoring stations are selected using U.S. EPA guidance and in general are established near populous areas or pollutant sources. This network contains 15 stations.

    The algorithms used by the Kentucky Air Monitoring Network to produce this data are not currently available.

    If the station reported the dew point, it was used. Otherwise, the dew point was calculated by UCAR/JOSS. The sea level pressure was calculated bu UCAR/JOSS when the station reported a station pressure. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    More information can be found on the Kentucky Air Monitoring Network webpage (KY, 2004).

    2.0.11 Konza Prairie Long Term Ecological Research (KONZA_LTER) Algorithms

    The purpose of the Konza Prairie Long Term Ecological Research (LTER) network is to monitor meteorological parameters in tallgrass prairie on a long term basis. The Konza Prairie Biological Station (KPBS) is representative of native tallgrass prairie in the Flint Hills of eastern Kansas. Because of the relatively steep topography and rocky soils characteristic of the region, this grassland has never been plowed. There is 1 KONZA_LTER station in this BAMEX 2003 Hourly Surface Composite.

    The following variables measured at the Konza LTER site were included in this BAMEX 2003 Hourly Surface Composite:

    Hourly precipitation for this site is not precise, so precipitation has not been included in this composite.

    The dew point was calculated by UCAR/JOSS from temperature and relative humidity using the formula from Bolton (1980).

    Methods

    A Campbell Scientific (CR-10) data logger continuously monitors air temperature, relative humidity, wind speed, and samples wind direction at hourly intervals. A microprocessor in the CR-10 manipulates the raw data and outputs the average air temperature, relative humidity, wind speed, and the sampled wind direction each hour.

    Routine Maintenance

    Clock mechanisms require rewinding each week and pens must be refilled with ink. The cassette tape on the CR-10 is changed every two months but may be left longer if necessary.

    The CR-10 is battery operated, as is the cassette recorder. The CR-10 output includes the battery voltage every 24 hours and the batteries are constantly charged using a 110 outlet. Desiccant packets are changed when necessary. Batteries in the cassette are changed when the indicator lights indicate low voltage or approximately every four months in summer and every two months in winter.

    Currently all chart changing and any changing of the cassette tape are done on Tuesdays since this is the day that the NADP samplers are serviced.

    For more information, see the Konza Prairie LTER Program Web Site (Konza, 2003). A picture of a Konza weather station can be found here

    2.0.12 Louisiana Agriclimatic Information System Network (LAIS) Algorithms

    The Louisiana Agriclimatic Information System (LAIS) is a network of automated weather stations operated by the LSU AgCenter. The network is managed by the Department of Biological and Agricultural Engineering (BAE). There are 21 LAIS stations included in this BAMEX 2003 Hourly Surface Composite. More information can be found on the LAIS website (LAIS, 2004).

    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.

    Description

    The LAIS is a network of electronic weather stations 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.

    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 are 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.

    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. At most locations, wind speed and direction are also measured at 3 meters. In this case the sensors are a Met One 014 anemometer and a Met One 024 vane.

    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.

    Barometric Pressure: All stations in the LAIS network also observe barometric pressure.

    Dew point and 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.

    2.0.13 Lower Colorado River Authority Network (LCRA) Algorithms

    The Lower Colorado River Authority (LCRA) network is a network of surface meteorological stations over the Lower Colorado River basin in central Texas. These stations report hourly. There are 103 LCRA stations included in this BAMEX 2003 Hourly Surface Composite.

    Instrumentation

    All the gauges have the same type of rain (Sutron tipping bucket), temperature, & humidity sensor. Most gauges have the same type of wind sensor (MetOne Sonic Windspeed & Direction). Not all gauges have every type of sensor. Many gauges do not have a wind sensor at all.

    The exact height of all the wind speed sensors is not known. LCRA attempts to install them at a consistent height but not all of them are. The height is not on record anywhere. The other sensors are not at a consistent height at all sites either. LCRA does not record elevations for their stations.

    More information can be found in the LCRA website(LCRA, 2004).

    2.0.14 Unidata Local Data Manager (LDM) World Meteorological Organization (WMO) (LDMSFCMETR) Algorithms

    The Unidata Local Data Manager (LDM) (Unidata, 2002 ) distributes World Meteorological Organization (WMO) Surface data. These data are ingested by UCAR/JOSS in ASCII WMO meteorological message structure format (NOAA/NWS, 2002). The primary feedset name is "WMO" which includes Public Product Service (PPS), Domestic Data Service (DDS), High resolution Data Service (HDS), and International Data Service (IDS) feedtypes. Only products that match the patterns ^S[AP].* .... ([0-3][0-9])([0-2][0-9]) and ^SX..81 .... ([0-3][0-9])([0-2][0-9]) are collected. In these patterns, S stands for surface, A for Aviation Routine Reports (FM 15 - METAR), P for Special aviation weather reports (FM 16 - SPECI), and X for miscellaneous text records. Only hourly METAR data are included in this dataset. For information on the METAR format see the ASOS User's Guide, appendix, and ready reference guide. (NOAA, 2003). Observing, reporting, and coding standards for surface-based meteorological observations from all federal agencies are defined in the Federal Meteorological Handbook 1. Special data and METAR data that do not fall on the hour are available in the dataset ' BAMEX 2003 Mesonet Surface Miscellaneous Composite'. For 20 minute METAR stations, the observation that falls between 15 minutes before the hour and the hour, inclusive, is included in this dataset. If there is no observation in this time period, then the observation closest to the hour and falling between 1 minute and 15 minutes after the hour is included in this dataset. All other observations are included in the 'BAMEX 2003 Mesonet Surface Miscellaneous Composite ' dataset. There are 783 LDMSFCMETR stations in this BAMEX 2003 Hourly Surface Composite.

    This dataset contains ASOS, AWOS (USDOT, 1988 ), and MANUAL stations. Station ID's are 3 characters long. Some networks use the 4-character ID to refer to these stations. To obtain the 4-character id, prepend a "K". For example, station ABR could also be referred to as station KABR.

    An error was discovered in the LDMSFCMETR processing. Due to a coding error, the record for the last hour of the last day an LDMSFCMETR station reported during the BAMEX time of interest was inadvertently deleted. As most LDMSFCMETR stations report for the entire BAMEX TOI, most of these missing records occur on July 6, 2003. A total of 783 records were deleted (one for each LDMSFCMETR station). This bug affects the BAMEX 2003 Mesonet Surface Meteorological (Hourly) Multi-Network Composite (but NOT the BAMEX 2003 Mesonet Surface Meteorological (Miscellaneous) Multi-Network Composite, and thus the BAMEX 2003 Mesonet Precipitation (Hourly) Multi-Network Composite and the BAMEX 2003 Mesonet Precipitation (Daily) Multi-Network Composite as well.

    2.0.15 Michigan Automated Weather Network (MAWN) Algorithms

    Information on the sensors and algorithms used to collect the MAWN data are available on the MAWN website via the "Maintenance Reports" link at each station. The elevations on the MAWN stations are not currently available. 33 stations in this network are included in this BAMEX 2003 Hourly Surface Composite.

    UCAR/JOSS calculates dewpoint from relative humidity and temperature included in the MAWN data. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    2.0.16 Missouri Air Monitoring Network (AIRQUAL_MO) Algorithms

    These stations are located throughout the state of Missouri. Information on the sensors and algorithms used to collect this Missouri Air Quality data are not currently available. All meteorological instruments are on 10 meter towers. 20 stations in this network are included in this BAMEX 2003 Hourly Surface Composite.

    UCAR/JOSS calculates sea level pressure when there is a measured pressure included in the AIRQUAL_MO data. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    More information on this network can be found on the Missouri Department of Natural Resources, Air and Land Protection Division, Monitoring Air Quality website.

    2.0.17 Missouri Commercial Agricultural Weather Station Network (MOCAWS)

    The Commercial Agricultural Program of the University of Missouri Extension and Missouri Climate Center operate the MOCAWS network to document environmental conditions to support agricultural operations. For more information see the Missouri Weather Stations web site (AgEBB, 2003). There are 21 MOCAWS stations in this BAMEX 2003 Hourly Surface Composite.

    The algorithms used to produce the Missouri Commercial Agricultural Weather Station Network (MOCAWS) hourly surface data are not currently available.

    The dew point was calculated.

    2.0.18 National Data Buoy Center Network (NDBC) Algorithms

    The National Oceanic and Atmospheric Administration (NOAA) National Data Buoy Center (NDBC), is a part of the National Weather Service (NWS). NDBC designs, develops, operates, and maintains a network of data collecting buoys and coastal stations. There are 6 NDBC stations included in this BAMEX 2003 Hourly Surface Composite.

    This data set contains hourly resolution surface meteorological data from the NDBC moored buoy Coastal Marine (C-MAN) network. These stations are located in and around the Great Lakes. Only land-based stations are included in this BAMEX 2003 Hourly Surface Composite. Buoy observations are included in the BAMEX 2003 Mesonet Surface Miscellaneous Composite dataset.

    All stations measure wind speed, direction, and gust; barometric pressure; and air temperature. All buoys and many C-MAN stations located in offshore areas operate on marine batteries which are charged by solar cells. Data collection, averaging, and formatting for satellite transmission are controlled by a payload computer system. On buoys, the payloads and batteries are located inside the hull; on C-MAN stations, they are located at the base of the tower.

    NDBC uses commercially available sensors such as anemometers to measure wind speed and direction and barometers to measure atmospheric pressure. Stations are serviced as required to repair damaged or degraded equipment. In addition, all buoys are serviced about every 2 years for routine maintenance and to install newly calibrated sensors. The Great Lakes buoys are retrieved every fall because of potential damage by ice.

    NDBC Data Flow

    The observations from moored buoys and C-MAN stations are transmitted hourly through NOAA Geostationary Operational Environmental Satellites (GOES) to a ground receiving facility at Wallops Island, VA, operated by the NOAA National Environmental Satellite, Data, and Information Service (NESDIS). These reports are immediately relayed to the NWS Telecommunications Gateway (NWSTG) in Silver Spring, MD, where the reports undergo automated quality control. Observations from smaller drifting buoys are transmitted through NOAA Polar Operational Environmental Satellites (POES) to NESDIS and then to the NWSTG via Service Argos (ARGOS), which adds location information. From the NWSTG, the data are transmitted via various communications networks to NDBC and NWS offices and posted on the Internet.

    NDBC controls the transmission, quality control, and archival of data from the NDBC computer center. NDBC also serves as a data assembly center for receiving, quality controlling, and disseminating measurement data from other stations owned and maintained by non-federal regional ocean observing systems, members of the U.S. Integrated Ocean Observing System (IOOS).

    For more information in the NDBC stations, including maintenance reports and current data, see the National Data Buoy Center website. Sensor and siting information can be found in the Measurement Descriptions and Units (NDBC, 2004) portion of this site.

    Air temperature sensor heights are listed on the above website. Dewpoint temperature is taken at the same height as the air temperature measurement. For C-MAN sites and Great Lakes buoys, the recorded pressure is reduced to sea level using the method described in NWS Technical Procedures Bulletin 291 (11/14/80). Wind speed and direction are averaged over an eight-minute period for buoys and a two-minute period for land stations. Information on the averaging methods used is available on the Measurement Descriptions and Units portion of the NDBC website.

    2.0.19 New Mexico State University (NMSU)

    The New Mexico Monitored Climate Station Network is a network of stations located across the state of New Mexico. Information about the network and pictures of the stations are available at the NMSU Network home page ( NMSU, 2003). There are 5 NMSU stations in this BAMEX 2003 Hourly Surface Composite.

    Instrumentation

    NMSU Standard Stations (see station list below) 

      Air Temperature
  Model: Campbell Scientific Model cs500 Probe
  Sensor Type: Thermistor Fenwall (UUT51J1)
  Siting: 1.5 m Above Surface
  Accuracy: +/-0.2 C

  Relative Humidity
  Model: Campbell Scientific Model cs500 Probe
  Sensor Type: Resistance Chip: Phys Chem PCRC11
  Siting: 1.5 m Above Surface
  Accuracy: +/-5% RH

  Precipitation
  Model: Campbell Scientific Model TE525 Rain Gage
  Sensor Type: Tipping Bucket With Event Counter
  Siting: Gage Top At 43 cm Above Surface
  Accuracy: +/-1mm

  Wind Speed
  Model: Met One Model 014A Wind Speed Sensor
  Sensor Type: Anemometer Using Reed Switch
  Siting: 3.75 m Above Surface
  Accuracy: +/-1.5%

  Wind Direction
  Model: Met One Model 024A Wind Direction Sensor
  Sensor Type: Wind Vane Attached To Potentiom
  Siting: 3.75 m Above Surface
  Accuracy: +/-5deg
    Station List 
    ----------------------------------------
Station Name              Station Type
----------------------------------------
Caprock                   RAWS
Clayton                   NMSU Standard 
Clovis                    NMSU Standard
Paduca                    RAWS
Tucumcari                 NMSU Standard

    UCAR/JOSS calculates dewpoint from relative humidity and temperature. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    Flags '*' and ' ' set by NMSU were translated to UCAR/JOSS Quality Control Flags as follows:

  • * -> E
  • ' ' -> U

    2.0.20 National Oceanic and Atmospheric Administration (NOAA) Forecast Systems Laboratory (FSL) Meteorological Assimilation Data Ingest System (MADIS)

    This dataset is a collection of data from many networks. The data are fed to JOSS over the LDM by the FSL Meteorological Assimilation Data Ingest System (MADIS). Some of these networks are themselves collections of data from unrelated sources. Each of these networks/subnetworks can contain different frequency data and different parameters. 930 stations from the MADIS LDM feed are included in this BAMEX 2003 Hourly Surface Composite.

    Conventions

    The hourly parameter value given in this composite is the value closest to the hour that falls at or after 45 minutes and before (but not at) 15 minutes after the hour. All other parameters are reported in the BAMEX 2003 Mesonet Surface Miscellaneous Composite dataset. MADIS QC flags are not carried forward to JOSS format. However, the MADIS QC summary value X "Failed QC stage 1", which is a gross limit check, has been used to mask out extremely unlikely data. If the data fails this check, it is set to missing. Precipitation data has not been included in this composite.

    For more information on these networks, see the FSL/MADIS Surface Network Information webpage (FSL, 2003).

    2.0.21 North Dakota Roadway Weather Information System (RWIS) Network Algorithms

    Information on the sensors and algorithms used to collect this North Dakota Roadway Weather Information System data are not currently available. 10 stations in this network are included in this BAMEX 2003 Hourly Surface Composite.

    Wind directions provided by the North Dakota RWIS are reported as one of the 8 cardinal directions. UCAR/JOSS converts these winds to their decimal equivalent with North being zero. Wind speeds reported as calm by North Dakota RWIS were set to zero in this composite.

    UCAR/JOSS only reports hourly records in this BAMEX 2003 Hourly Surface Composite. If a record was not found exactly on the hour, the nearest record in the ten minutes before the hour was used followed by the 5 minutes after the hour. If there was not a record in this 15 minute interval, there is no record reported for that hour in this composite. Records that did not fall on the hour are reported in the BAMEX 2003 Mesonet Surface Miscellaneous Composite.

    RWIS often does not record elevations for their stations.

    For more information on this network, see the ND RWIS webpage.

    2.0.22 Ohio Agricultural Research & Development Center (OARDC) Algorithms

    In 1980, a network of automated weather stations was established in Ohio in a cooperative research effort between OARDC and Miami University. In 2002, USDA set up stations at nurseries, and OARDC cooperated with them to make the data available online. These new stations (Avon, Perry and Madison aka SUNLEAF) are updated every 15 minutes and the data are available here in a graphical format. The purpose of this network was to obtain a geographically comprehensive and cohesive set of Ohio climatic data for research purposes. Please note that these data are gathered automatically by computers and remote sensors and do not represent official U.S. Weather Bureau records.

    The network now consists of 15 stations, 13 of which are automated, and most of which are located at OARDC branch campuses. 11 of these stations are included in this BAMEX 2003 Hourly Surface Composite. Instrumentation at the stations is consistent.

    OARDC does not change the data, but if they become aware of a data problem, the affected data are deleted. One exception is that any RH over 100% is reported as 100.

    Instrumentation:

    Since the weather stations were established in support of agricultural research, instrumentation was designed to provide the data elements most critical for this purpose. Each station is equipped with a DC-powered Campbell Scientific datalogger and a DC-powered modem to provide data storage and transmittal to the central computer storage facility on the Wooster campus of the OARDC. The dataloggers are able to retain almost one month of hourly data.

    Instrumentation includes sensors to measure temperature and relative humidity in a non-aspirated shelter at 1.5m; wind speed and wind direction at 5 m, and precipitation at 1 m. UCAR/JOSS calculates dewpoint from relative humidity and temperature. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    All the off-hour data for stations which report at 15 minute intervals have been included in the BAMEX 2003 Mesonet Surface Miscellaneous Composite Stations PERRY and SUNLEAF have missing elevations. There are no provided elevations for these stations.

    For more information and current data, please visit the OARDC website (OARDC, 2004)

    2.0.23 Ohio Air Monitoring Network (AIRQUAL_OH) Algorithms

    This data set contains hourly resolution surface meteorological data from the Ohio Environmental Protection Agency (EPA) air monitoring network. These OARDC stations are located across the state of Ohio. The network consists of five stations located primarily in or near urban areas.

    Instrumentation

    Information on instrumentation can be found in the following pdf files:

  • WSWDSite.pdf- A document containing site information.
  • WSWDmon.pdf- A document containing site monitor information.
  • WSWDsum.pdf- A document containing what parameters each station reports.

    For more information, please visit the Ohio EPA website

    2.0.24 Ohio Roadway Weather Information System (RWIS) Network Algorithms

    This network contains surface meteorological data from 62 stations in the Ohio Road Weather Information System (RWIS) operated by the Ohio Department of Transportation. The network includes stations along roads throughout the state of Ohio.

    Instrumentation

    All the atmospheric instruments are made by Vaisala, Inc. and are mounted on a pole 20' in the air. RWIS does not record elevations for their stations.

    Wind direction is a two-minute average of the direction from which the wind is blowing measured clockwise in degrees from true North Wind speed is a two minute average of the wind speed Gust speed is the maximum wind gust recorded during the 10 minutes preceding the observation.

    Air temperature is the instantaneous dry-bulb temperature The dewpoint temperature is also an instantaneous reading. When dewpoint temperature was not available, it was calculated by UCAR/JOSS from the relative humidity and temperature. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    Surface visibility is measured to one tenth of a meter.

    UCAR/JOSS only reports hourly records in this BAMEX 2003 Hourly Surface Composite. If a record was not found exactly on the hour, the nearest record in the ten minutes before the hour was used followed by the 5 minutes after the hour. If there was not a record in this 15 minute interval, there is no record reported for that hour in this composite. Records that did not fall on the hour are reported in the BAMEX 2003 Mesonet Surface Miscellaneous Composite. If there are two records with the same actual time for a station, the first one in the file is selected. The other record is placed in the BAMEX 2003 Mesonet Surface Miscellaneous Composite

    More information on the Ohio RWIS network can be found on the Ohio Department of Transportation Buckeye Traffic website.

    2.0.25 Purdue Automated Agricultural Weather Station (PAAWS) Network Algorithms

    This data set contains surface meteorological data from the Purdue Automated Agricultural Weather Station (PAAWS) Network. This network includes 7 stations around the state of Indiana. The PAAWS network is a system of remote automatic weather stations located at each of the eight regional Purdue Agricultural Research Centers (ARCs) throughout Indiana and the Purdue Agronomy Research Center. The purpose of the network is to continuously measure weather elements of special interest to Purdue agricultural researchers.

    Instrumentation

    Each automatic weather station datalogger measures wind direction and speed at 10', air temperature at 4.5 ', and precipitation, as well as other parameters that are not included in this composite.

    Most weather sensors and the datalogger are mounted on a 10 foot high tower mast. The wind vane and cup anemometer are mounted on a crossarm at the top of the mast. A cell phone antenna is also mounted on the mast.

    Mounted lower on the mast is the air temperature sensor, a thermistor shielded by an enclosure to avoid exposure to sunlight.

    The Zeno datalogger is mounted in an enclosure on the mast a few feet above the ground. All sensor leads run into the enclosure. The cell phone transceiver and modem are also inside the datalogger enclosure with a lead to the outside antenna. The voice synthesizer is located inside the enclosure as well.

    The raingage is located about 20 feet away from the tower mast, with its leads buried underground. The gage has a very low profile, with its top funnel opening just one foot above ground level.

    Wind Speed and Direction Sensor Information

    Wind direction is measured by a conventional balanced wind vane, sensitive to winds of at least 3 mph. The circular position of the wind vane is converted to an electrical signal by a conductive plastic potentiometer. A 15 volt signal is applied to the potentiometer. A percentage of this voltage is output by the potentiometer, directly related to the wind direction angle.

    A limitation of this sensor is that the potentiometer becomes worn over time, resulting in noisy or non-linear output. The only remedy is to replace the potentiometer.

    Wind speed is measured by a conventional rotating cup anemometer. As the cups rotate they produce an AC sine wave voltage signal with its frequency directly related to the wind speed. One complete sine wave corresponds to one rotation of the cup wheel. The AC sine wave is induced in a stationary coil by a two pole ring magnet mounted on the cup wheel shaft.

    A limitation of this sensor is that the precision ball bearings become worn rather quickly. As bearings wear they become noisy or the minimum detectable wind speed increases above an acceptable level. New bearings give the anemometer a starting speed of 2.5 mph, indicating it will start turning from a calm situation when wind speeds exceed 2.5 mph. Lower wind speeds are measureable if the winds were first above 2.5 mph. Bearings will be replaced at least yearly and probably twice a year.

    The measurement of wind gusts is highly sensitive to the number of samples included in a running average of wind speed. Our dataloggers at each Purdue ARC have been set to average the last 4 seconds of instantaneous samples when calculating wind gust. This is the factory recommended setting. A longer averaging period, such as the 5 seconds used by the National Weather Service in their automated ASOS system, will nearly always result in lower gust values. The National Weather Service will soon make a decision on whether to shorten the averaging time to 3 seconds, at the request of some of their field offices.

    Air Temperature Sensor Information

    Air sensors are sheltered by a 6-plate passive ventilation shield to avoid exposure to sunlight.

    Thermistors are sensitive to small changes in temperature. The sensors used in this project are precisely manufactured so that they are directly interchangable should sensors require replacement. All thermistors are calibrated at the factory be measuring at multiple temperatures to insure that the sensor resistance and slope meet the device's interchangability specification.

    Thermistors cannot be repaired. Faulty devices must be replaced in their entirety.

    Precipitation Sensor Information

    Precipitation is measured by a miniture version of the standard National Weather Service tipping bucket electronic raingage.

    The sensor has an aluminum collector funnel with a knife edge that directs incoming water into twin tiny buckets able to hold exactly .01 inch of water and counter-balanced on a central pivot. As one of the two chambers fills, it tips, spilling out to the bottom of the housing. A magnet is attached to a tipping bucket, which as the bucket tips, triggers a magnetic switch. A momentary switch closure occurs with each tip, which the datalogger senses and so increments an event counter.

    The alternate bucket is now exposed and begins to collect the next .01 inch of precipitation. After this bucket fills and tips the first bucket is returned to its original position and the whole cycle repeated. The total events counted at the end of a reporting period corresponds to precipitation accumulation in units of hundreths of inches. After the report the event counter is reset to zero.

    The tipping bucket has several limitations. First, the sensor must be kept clean. Any accumulation of bugs, dust, twigs, and other material can invalidate its measurements. Second, the tipping bucket has a maximum reliable flow rate of one inch of rain per hour. In more intense rain events the instrument will read low as a fixed amount of time is required for the bucket to tip and position the alternate bucket in place. Intermediate rainfall will be lost as water flows into the buckets rather than drips.

    The third deficiency of the tipping bucket is it does not work well in frozen precipitation events. Thus precipitation reports printed by the Indiana Climate Page when the air temperature is below freezing should be discarded. The data are suspect.

    This winter limitation could be partly resolved by adding heat tape around the gage funnel. This is not a foolproof solution, however, and creates its own set of problems. We have chosen to not install heat tape in the tipping bucket gages at any of the ARCs. Cold season precipitation data should be ignored as being unreliable.

    Purdue Processing

    All weather sensor sampling, data storage, and data retrieval at the weather station is controlled by a datalogger, the Zeno 3200, manufactured by Coastal Environmental Systems of Seattle, Washington.

    Once each second the Zeno samples each weather sensor. The data are calibrated from electrical units (such as volts) into meteorological units (such as temperature degrees).

    Each weather sample may undergo further evaluation at this time depending on what type of sensor is involved and what extended processing the Zeno software manager has instructed the datalogger to do for that sensor. The results of all such Zeno sampling and processing are stored in its internal memory until the end of the sampling period is reached.

    The Zeno software manager can instruct the datalogger how long to continue sampling until a summary report is generated. The Zenos at the Purdue ARCs have been set to sampling periods of 30 minutes. At the end of each half hour, a summary table is generated which includes 30-minute averages of wind direction and speed, and air temperature. The extreme wind gust for the 30-minute period, and the total precipitation are also calculated into the summary table.

    Whenever the datalogger senses that something is wrong with one of its weather sensors, it flags that value in its memory as being suspect. The limits on when a sensor is considered suspect may be set by the datalogger manager.

    In most cases Purdue has accepted the factory defaults as to when a sensor is flagged. There are two circumstances in which a sensor is flagged. First, the sensor values have gone out of range, either too high or low to be regarded as reasonable under typical Indiana weather conditions. Second, the sensor value has been "stuck" or "nearly stuck" on one value much too long. This sensor is expected to vary in value quite frequently in Indiana but it has not. This may be a bad sensor or a sensor which has frozen over (in winter) and is no longer responsive to true environmental conditions.

    In any event any value which is flagged in the summary table should be used with caution. A flagged value in the hourly or daily option tables indicates that at least one value in the 30-minute source data from which the hourly or daily table was calculated was flagged.

    The methods used by PAAWS to convert 30-minute data to hourly are not currently available. UCAR/JOSS includes the hourly data in this BAMEX 2003 Hourly Surface Composite.

    More information on the PAAWS network can be found on the PAAWS Network Home Page (PAAWS, 2004)

    2.0.26 South Dakota Roadway Weather Information System (RWIS) Network Algorithms

    This data set contains hourly resolution surface meteorological data from the South Dakota Road Weather Information System (RWIS) operated by the South Dakota Department of Transportation. The network includes 18 stations located throughout the state of South Dakota.

    Instrumentation

    The data source has no information on instrumentation.

    UCAR/JOSS calculates dewpoint from relative humidity and temperature. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    Records that did not fall on the hour are reported in the BAMEX 2003 Mesonet Surface Miscellaneous Composite.

    The SD RWIS home page contains current measurements from the SD RWIS sites.

    2.0.27 Texas North Plains Potential Evapotranspiration (PET) Network

    Potential EvapoTranspiration or PET is the amount of evaporation and transpiration a well-watered plant has daily and throughout its typical growing season. Transpiration is the water entering the plant root system and used to build plant tissue or being passed through the leaves into the atmosphere. Evaporation is the water evaporating from the adjacent soil, water surfaces, or from the surface of leaves of the plant. There are 15 PET stations in this BAMEX 2003 Hourly Surface Composite.

    The PET system has a network of weather stations located throughout the North Plains of Texas whereby PET calculations are made and disseminated in an automated process providing timely, accurate, predicted evapotranspiration data. Several microcomputers and software programs are utilized in the sequence of data manipulation, reduction, and computation.

    The network operates weather stations in irrigated crop-growing regions across the central and northern Texas Panhandle.

    Instrumentation

    The stations are Campbell Scientific Inc WW2000 or MetData1 systems reduced to 2 meter towers or at least mimic them with the same instruments. Heights are 1.8 to 2 meters above ground level for all data.

    UCAR/JOSS calculates sea level pressure and dewpoint. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    For more information on the PET network see the TX North Plains ET Network Home Page ( Texas A&M, 2003).

    2.0.28 Texas West Texas Mesonet (WTXMESO) Algorithms

    This data set contains hourly resolution surface meteorological data from the West Texas Mesonet operated by Texas Tech. The West Texas Mesonet includes 38 stations in the region around Lubbock, Texas.

    Instrumentation

    Each mesonet station consists of a fenced 10x10 meter plot of land, 10 meter tower, solar panel, RF modem and antenna.

    Instrumentation for a basic mesonet station follows:

    UCAR/JOSS calculates the dewpoint and sea level pressure. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2 .

    The West Texas Mesonet reports data at 5-minute intervals. UCAR/JOSS takes the report falling closest to the hour and includes it in this BAMEX 2003 Hourly Surface Composite. Records that did not fall on the hour are reported in the BAMEX 2003 Mesonet Surface Miscellaneous Composite

    For information on, and to access, data and parameters not included in this BAMEX 2003 Hourly Surface Composite, see the BAMEX Mesonet: Texas West Texas Mesonet Data [Texas Tech] dataset

    For more information see the West Texas Mesonet home page (Texas Tech University, cited 2003).

    2.0.29 Texas Natural Resource Conservation Comission (TNRCC) Algorithms

    This data set contains hourly resolution surface meteorological data from the Texas Natural Resources Conservation Commission (TNRCC) Air Quality Monitoring Network. This BAMEX 2003 Hourly Surface Composite includes 44 TNRCC stations from around the state of Texas.

    Instrumentation

    The instrumentation is the same at all sites. The wind and temperature instruments are located at the top of 10 meter towers at all sites.

    UCAR/JOSS calculates the dewpoint, when dewpoint is not available in the raw data, and sea level pressure. For information on the calculation of parameters derived by UCAR/JOSS from the raw parameters available, see Section 2.2.

    Data quality flags provided by the source were used to assign JOSS data quality flags in this BAMEX 2003 Hourly Surface Composite using the following scheme: data values flagged 'FEW' by the source were assigned the 'I' flag, and data values flagged 'QAS|QRE|PMA|LST|AQI|LIM' by the source were assigned the 'M' flag, in this BAMEX 2003 Hourly Surface Composite.

    For more information view the TNRCC Air Monitoring Home Page.

    2.0.30 Wisconsin Automated Weather Observation Network (WI_AWON) Algorithms

    Since 1985, the University of Wisconsin - Extension has maintained a system of automated weather stations in Wisconsin to provide meteorological data for agriculture and agricultural research. Two stations from this University of Wisconsin Automated Weather Observation Network are included in this BAMEX 2003 Hourly Surface Composite.

    WI AWON reports data at 30 minute intervals. UCAR/JOSS reports hourly data in this BAMEX 2003 Hourly Surface Composite. Records that did not fall on the hour are reported in the BAMEX 2003 Mesonet Surface Miscellaneous Composite.

    The algorithms used to produce the WI AWON data are not currently available. Wisconsin AWON does not report elevations.

    The AWON website is www.soils.wisc.edu/wimnext/awon/awon.html

    2.0.31 Hourly Surface data extracted from the BAMEX 2003 Mesonet 1-Minute Surface Meteorological Composite

    This dataset is formed by extracting Hourly Surface Meteorological Data from the BAMEX 2003 Mesonet 1-Minute Surface Meteorological Composite. Refer to the BAMEX 2003 Mesonet 1-Minute Surface Meteorological Composite description document for more information.

    Data from five DOE Atmospheric Boundary Layer Experiments (ABLE) Automated Weather Stations (AWS) were extracted from the one minute Meteorological Composite and included in this BAMEX 2003 Hourly Surface Composite. More information on ABLE AWS can be found on the ABLE Home Page (ANL, 2004).

    An hourly file is created from a 1-minute file by selecting the (xx-1):55 observation as the xx hourly observation, with the exception of the precipitation parameter, which is totaled from (xx-1):01 through xx:00 (where xx is the 2-digit hour and xx-1 is the previous hour), and placed in the xx hourly observation. So the 2PM hourly observation contains the 1:55 1-minute observation for all parameters except precipitation. The 2PM hourly precipitation value is a sum of all 1-minute precipitation values from 1:01 to 2:00 inclusive. If any 1-minute precipitation values in this range are missing, then the hourly value is set to missing.

    2.1 Detailed Format Description

    The BAMEX 2003 Hourly 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. Days begin at UTC 0100 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. 

         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

    This dataset contains only the "Nominal" hourly observations for the BAMEX 2003 domain and time period. Other records, including special records and records not included in this composite, are located in the BAMEX 2003 Mesonet Surface Miscellaneous Composite dataset.

    Sea Level Pressure is calculated from station pressure using standard GEMPAK algorithms (Unidata, 2003).

    When not present in the raw data, the dewpoint temperature was computed by UCAR/JOSS from temperature and relative humidity using the formula from Bolton (1980).

    When not present in the raw data, station pressure is computed by UCAR/JOSS from altimeter and elevation using the formula from the Smithsonian Meteorological Tables, 1949.

    An error was discovered in the LDMSFCMETR processing. Due to a coding error, the record for the last hour of the last day an LDMSFCMETR station reported during the BAMEX time of interest was inadvertently deleted. As most LDMSFCMETR stations report for the entire BAMEX TOI, most of these missing records occur on July 6, 2003. A total of 783 records were deleted (one for each LDMSFCMETR station). This bug affects the BAMEX 2003 Mesonet Surface Meteorological (Hourly) Multi-Network Composite (but NOT the BAMEX 2003 Mesonet Surface Meteorological (Miscellaneous) Multi-Network Composite, and thus the BAMEX 2003 Mesonet Precipitation (Hourly) Multi-Network Composite and the BAMEX 2003 Mesonet Precipitation (Daily) Multi-Network Composite as well.

    3.0 Quality Control Processing

    The BAMEX 2003 Hourly Surface Composite was formed from several datasets. These BAMEX 2003 Hourly Surface Composite datasets were collected over the BAMEX 2003 domain (i.e., 30N to 48N latitude and -104 to -80W 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 Hourly Surface Composite.

    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 1.2 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 sea level 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 pressure. 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.

    Table 3-1 Normalizing factors used for BAMEX 2003 Hourly Surface Composite 

         Parameter                  Good      Questionable   Unlikely
     ---------                  ----      ------------   --------
     Station Pressure           0.2           0.2          0.5
     Sea Level Pressure (SLP)   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 Hourly Surface Composite 

         
     Parameter                      Good      Questionable   Unlikely
     ---------                      ----      ------------   --------

     Station Pressure (mb)         < 1.2       [0.5-2.9]      > 1.1
     Sea Level Pressure (mb)       < 1.2       [0.5-3.0]      > 1.1
     Calculated SLP (mb)           < 2.6       [0.9-6.4]      > 2.2
     Dry Bulb Temperature (deg.C)  < 2.7       [0.9-5.3]      > 1.7
     Dew Point Temperature (deg.C) < 2.7       [0.9-5.4]      > 1.7
     Wind Speed (m/s)              < 6.2       [0.5-11.0]     > 0.9
     Wind Direction(degrees)       < 156.7     [72.2-180.0]   >130.2


    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 

         
     Parameter              Good      Questionable     Unlikely
     ---------              ----      ------------     --------
     Hourly Precipitation  < 20.0 mm   >= 20.0 mm      >= 50.0 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

    Agricultural Electronic Bulletin Board (AgEBB), cited 2003: Missouri Weather Stations [Available online from http://agebb.missouri.edu/weather/stations/]

    Argonne National Laboratory, cited 2004a: ABLE Automatic Weather Station (AWS) [Available online from http://www.atmos.anl.gov/ABLE/aws.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]

    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.

    Campbell Scientific, cited 2003: MetData1 Weather Station [Available online from http://www.campbellsci.com/p-weatherstations.html#metdata1]

    Colorado State University (CSU), Cited 2004: CoAgMet Homepage [Available online from http://ccc.atmos.colostate.edu/~coagmet/].

    Cressman, G. P., 1959: An operational objective analysis system. Mon. Wea. Rev., 87, 367-374.

    FSL, cited 2003: Meteorological Assimilation Data Ingest System (MADIS) Surface Network Information [Available online from http://www-sdd.fsl.noaa.gov/MADIS/network_info.html]

    GLERL, cited 2004: GLERL Realtime Meteorological Observation Network [ Available online from http://www.glerl.noaa.gov/metdata]

    High Plains Regional Climate Center (HPRCC), cited 2003: Automated Weather Data Network [Available online from http://hpccsun.unl.edu/awdn/]

    Hollinger, Steven E., Reinke, Beth C., and Peppler, Randy A. Illinois Climate Network: Site Descriptions, Instrumentation, and Data Management. Illinois State Water Survey, Champaign, IL., Circular 178. 1994.

    IEM, cited 2004: Iowa Environmental Mesonet School Network [Available online from http://mesonet.agron.iastate.edu/schoolnet]

    Illinois, 2003: Illinois Annual Air Quality Report 2003 [Available online from http://www.epa.state.il.us/air/air-quality-report/2003/air-quality-report-2003.pdf ]

    Konza Prairie LTER Program, cited 2003 [Available online from http://www.konza.ksu.edu/]

    KY, 2004: KY Division for Air Quality, Ambient Air Monitoring [Available online from http://www.air.ky.gov/programs/monitoring]

    LAIS, 2004:Louisiana Agriclimatic Information [Available online from http://www.agctr.lsu.edu/weather]

    LCRA, 2004 [Available online from http://www.lcra.org/water/index.html]

    NDBC, 2004: Measurement Descriptions and Units [Available online from http://www.ndbc.noaa.gov/measdes.shtml]

    NMSU, cited 2003: New Mexico Climate Center [Available online from http://weather.nmsu.edu/]

    NOAA, National Weather Service, Automated Surface Observing System (ASOS), cited 2003: ASOS User's Guide

    NOAA/NWS, cited 2002: WMO Message structure 2000 Paraphrased Version [Available online from http://www.nws.noaa.gov/tg/head.html].

    OARDC, 2004: OARDC Weather Stations [Available online from http://www.oardc.ohio-state.edu/centernet/weather.htm ]

    PAAWS, 2004: PAAWS, Purdue Automated Agricultural Weather Stations network [Available online from http://shadow.agry.purdue.edu/sc.zen-geog.html]

    Smithsonian Meteorological Tables, Table No. 65, p.269. Smithsonian Institution Press, Washington, D.C., September, 1949.

    Texas A&M, 2003: TX North Plains ET Network Home Page [Available online from http://amarillo2.tamu.edu/nppet/petnet1.htm]

    Texas Tech University, cited 2003: West Texas Mesonet home page [Available online from http://www.mesonet.ttu.edu/]

    Unidata, Cited 2002: Unidata LDM [Available online from http://www.unidata.ucar.edu/packages/ldm/].

    Unidata, Cited 2003: Unidata 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.

    World Meteorological Organization (WMO), 1988: Manual on Codes Volume I, Part B - Binary Codes. WMO, Geneva, Switzerland.