Lake-ICE Hourly Surface Composite 1.0 General Description The Lake-Induced Convection Experiment Hourly Surface Composite is composed of data from several sources (i.e., Automated Surface Observing System (ASOS), High Plains Climate Network (HPCN), Great Lakes Environmental Research Laboratory (GLERL), NOAA Profiler Network (NPN), Illinois Climate Network (ICN), University of Wisconsin Agricultural Weather Observation Network (AWON), and the National Climatic Data Center (NCDC) DATSAV2) for the Lake-ICE domain. Data from these sources (1105 stations) were quality controlled with the data from the Lake-ICE 5-Minute Surface Composite and the Lake-ICE 20- Minute Surface Composite. This Hourly Surface Composite contains data for the Lake-ICE time period (28 November 1997 through 25 January 1998) and for the Lake-ICE domain. The Lake-ICE domain is approximately 37N to 55N latitude and 73W to 104W longitude. 2.0 Detailed Data Description The Lake-ICE Hourly Surface Composite is composed of data from several different sources which report data at hourly frequencies. 2.0.1 Automated Surface Observing System (ASOS) Algorithms The following are descriptions of the algorithms used by ASOS to produce hourly surface data. Complete details may be found in the ASOS User's Guide (1992). The ASOS hourly values were produced from ASOS 5-minute data by extracting all parameters (except precipitation) from the 55-minute observation of the previous hour and assigning those values to the current hourly observation. The precipitation is the sum of the precipitation values from the 05-minute of the previous hour through the 00-minute of the current hour. The descriptions of the algorithms used by ASOS to produce five minute surface data are given in the Lake-ICE 5-Minute Surface Composite description document. 2.0.2 High Plains Climate Network (HPCN) Algorithms The algorithms used to produce the High Plains Climate Network hourly surface data are not currently available. The High Plains Climate Network reports only the moisture measurement of relative humidity, and does not report any pressure parameter. This hourly composite includes dew point as the moisture parameter. To convert relative humidity to dew point, the station elevation and the standard atmosphere were used to generate an estimate of the station pressure, which was then used in the relative humidity to dew point conversion. 2.0.3 Great Lakes Environmental Research Lab (GLERL) Algorithms The algorithms used to produce GLERL Network hourly surface data are not currently available. 2.0.4 NOAA Profiler Network (NPN) Algorithms The algorithms used to produce NOAA Profiler Network hourly surface data are not currently available. 2.0.5 Illinois Climate Network (ICN) Algorithms The Illinois Climate Network (ICN) collects hourly air temperature, relative humidity, barometric pressure, precipitation, and wind speed and direction. The algorithms used to produce this surface data are discussed below. The data from this network of mesonet stations were obtained from the Illinois State Water Survey. Complete details can be found in Illinois Climate Network: Site Descriptions, Instrumentation, and Data Management (1994). Temperature/Relative Humidity Air temperature and relative humidity are monitored using a Vaisala temperature and humidity probe. The operating temperature is from -5 to +55 degrees C, and 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. The temperature accuracy is considered suitable for automated stations used for synoptic meteorology, and the humidity accuracy is considered suitable for climatology work. ICN notes that some sensors have been in the field for more than a year without significant drift or failure. Hourly averages are computed using 10-second samples. Station Pressure A Campbell Scientific SBP270 barometric pressure sensor is used to measure barometric pressure at each ICN station. The accuracy of the sensor is +/- 0.2 MB over a pressure range of 800 to 1000 mb. Operating temperature of the sensor is -18 to 979 degrees C. The barometer in the sensor is a Setra Model 270 variable capacitance barometer. The reported pressure is then used in the computation of derived parameters. Hourly averages are computed using 10-second samples. Wind Wind speed and direction are monitored with an R. M. Young 8003 anemometer fitted with a wide range molded polypropylene plastic 4 blade propeller. The anemometer has a functional wind speed range of 0 to 50m/s, with a threshold speed of 0.2 to 0.4 m/s. Wind direction is measured from 0 to 355 degrees. A 20K 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. A direction signal of zero represents north. Rotation of the vane in a clockwise direction causes the azimuth signal to increase in value until the vane reaches 355 degrees, where the signal falls to zero. Hourly averages are computed using 10-second samples. Precipitation A Belfort weighing bucket rain gage fitted with an eight-inch collector opening and a potentiometer is used to measure precipitation at each site. Precipitation is determined by subtracting the weight of water collected in a bucket at the end of an hour from the weight at the beginning of an hour. Negative hourly observations are assumed to be zero and are due to "noise" such as evaporation or electrical noise in the instrument. The maximum collection capacity for each raingage is twelve inches. Present Weather Present weather is not reported in the ICN data. 2.0.6 University of Wisconsin AWON Algorithms The algorithms used to produce University of Wisconsin AWON Network hourly surface data are not currently available. 2.0.7 National Climatic Data Center (NCDC) DATSAV2 Algorithms The NCDC DATSAV2 Surface Database is composed of worldwide surface weather observations collected and stored from several sources (including from Global Telecommunications System (GTS)) since 1973. Most collected observations are decoded at the Air Force Global Weather Central (AFGWC) then sent to the United States Air Force Environmental Technical applications Center's Operating Location A (OL-A) at Asheville, North Carolina. At OL-A the observations are processed into the DATSAV2 Surface Database format for database storage, and DATSAV2 refers to the digital tape format in which decoded weather observations are stored at OL-A. DATSAV2 is the official climatological database for surface observations such as synoptic, airways, Meteorological Aviation Routine Weather Reports (METAR), Aviation Routine Weather Report (AERO), Supplementary Marine Reporting Station (SMARS), as well as observations from automatic weather stations. OL-A sorts the observations into station-date-time order, and validates each block-station number against the Air Weather Service Master Station Catalog (AWSMSC). OL- A merges and sorts the data into monthly and yearly station-ordered files and processes the data through several quality control programs. For more information about the DATSAV2 format and the quality control performed on this data see USAF, 1986. 2.1 Detailed Format Description The Lake-ICE Hourly Surface Composite 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 hour 0100 and end at UTC hour 0000 the following day. The data parameters are valid for the reported times. Missing values are reported as 9's in the data field. The table below details the data parameters in each record. Several data parameters have an associated Quality Control (QC) Flag Code which is assigned during the Joint Office for Science Support (JOSS) quality control processing. 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 When not present in the raw data, the dew point is computed using the formula from Bolton (1980). Calculated Sea Level pressure is computed from station pressure, temperature, dew point, and station elevation using the formula of Wallace and Hobbs (1977). 3.0 Quality Control Processing The Lake-ICE Hourly Surface Composite was formed from several datasets (I.e., Automated Surface Observing System (ASOS), High Plains Climate Network (HPCN), Great Lakes Environmental Research Laboratory (GLERL), NOAA Profiler Network (NPN), Illinois Climate Network (ICN), University of Wisconsin AWON, and National Climatic Data Center (NCDC) DATSAV2 for the Lake-ICE domain (i.e., 37N to 55N and 73W to 104W) and time period (28 November 1997 through 25 January 1998). The data from the Lake-ICE Hourly Surface Composite, Lake-ICE 20-Minute Surface Composite, and the Lake-ICE 5-Minute Surface Composite were quality controlled together. The 5-minute, 20-minute, and Hourly data were then divided into their respective composites. 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 300 km Radius Of Influence (ROI) centered about the station being quality controlled (the station being quality controlled was excluded); i.e.; theta_e = / 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 Lake-ICE 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 Lake-ICE data fell within these ranges. For example, 95% of the observed station pressure values that were flagged as "good" were within 1.6 mb of the expected value. The significant overlap of the ranges seen in Table 3-2 was partially due to seasonal and station differences in standard deviations. The actual HQC limits applied at any particular time depended upon the dynamic nature of the particular station's parameter values over time. Data were never changed, only flagged. HQC was only applied to station pressure, 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 and sea level pressures. If the calculated sea level pressure could not be quality controlled, the sea level pressure quality control flag was applied to the station pressure. If the sea level pressure could not be quality controlled, the station pressure quality control flag was not overridden. Table 3-1 Normalizing factors used for Lake-ICE 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 Lake-ICE Hourly Surface Composite Parameter Good Questionable Unlikely --------- ---- ------------ -------- Station Pressure (mb) < 1.7 [0.8-4.1] > 2.1 Sea Level Pressure (mb) < 1.9 [0.9-4.9] > 2.2 Calculated SLP (mb) < 3.6 [1.8-8.9] > 4.6 Dry Bulb Temperature (deg.C) < 3.8 [1.0-7.6] > 2.0 Dew Point Temperature (deg.C) < 4.2 [1.1-8.4] > 2.2 Wind Speed (m/s) < 7.0 [2.8-12.5] > 4.9 Wind Direction(degrees) < 173.6 [94.5-180.] > 170.4 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". The meanings of the possible quality control flags are listed in table 3-4. Table 3-3 - Precipitation Gross Limit Values Parameter Good Questionable Unlikely --------- ---- ------------ -------- Hourly Precipitation < 3 mm 3-6 mm >= 6 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 ASOS User's Guide, ASOS Project Office, NOAA, National Weather Service, Washington D.C., June 1992. Barnes, S. L., 1964: A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor., 3, 396-409. Bolton, D., 1980: The computation of equivalent potential temperature., Mon. Wea. Rev., 108, pp 1046-1053. Cressman, G. P., 1959: An operational objective analysis system. Mon. Wea. Rev., 87, 367-374. Illinois Climate Network: Site Descriptions, Instrumentation, and Data Management, Illinois State Water Survey, Champaign, Illinois, Circular 178, 1994. United States Department of Commerce, 1988: Federal Meteorological Handbook Number 1, Surface Observations. National Oceanic and Atmospheric Administration, Washington, D.C., April 1988. United States Air Force Environmental Technical Applications Center OL-A, 1986: USAFETAC Climatic Database Users Handbook No. 4. United States Air Force, Asheville, N.C., December 1986. Wallace, J.M., P.V. Hobbs, 1977: Atmospheric Science, Academic Press, 467 pp. World Meteorological Organization (WMO), 1988: Manual on Codes Volume I, Part B - Binary Codes. WMO, Geneva, Switzerland.