The Creation of an Historical Meteorological Database for Environmental Dose Assessment

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    1 Savannah River Technology Center, Westinghouse Savannah River Company, Aiken, SouthCarolina, U.S.A.; 2 Oregon State University, Nuclear Engineering and Radiation Health Physics,

    Corvallis, Oregon, U.S.A.( author for correspondence, e-mail:

    (Received 7 November 2001; accepted 7 June 2002)

    Abstract. The focus of this study is to develop wind data for the Savannah River Site (SRS) between1955 and 1961 to be used in an assessment of estimates of atmospheric dispersion and downwind riskat the Savannah River Site. In particular, a study of the uncertainties of radioiodine dosimetry fromthe late 1950s provides the underlying motivation for developing historical windroses at the SavannahRiver Site (SRS). Wind measurement towers did not exist at the SRS until the early 1970s. Threerelatively simple methods were used to create a 19551961 meteorological database for the SRS fora dose reconstruction project. The winds were estimated from onsite measurements in the 1990s andNational Weather Service (NWS) observations in the 1990s and 1950s using (1) a linear regressionmethod, (2) a similarity theory approach, and (3) a simple statistical differences method. The criteriafor determining success were based on (1) how well the mean values and standard deviations of thepredicted wind speed agree with the known SRS values from the 1990s, (2) the shape of the pre-dicted frequency distribution functions for wind speed, and (3) how closely the predicted windrosesresembled the SRS windrose for the 1990s. The linear regression models wind speed distributionfunction was broad, flat, and skewed too much toward higher wind speeds. The similarity theoryapproach produced a wind speed distribution function that contained excess predicted speeds in therange 01.54 m s1 (03 kts) and had excluded bins caused by predictions being made from integervalues of knots in the NWS data. The distribution function from the mean difference method wassmooth with a shape like a Weibull distribution with a shape parameter of 2 and appeared to resembleclosely the SRS 19921996 distribution. The wind directions for all three methods of approach weresuccessfully based on the mean difference method. It was difficult to discern differences amongthe wind roses produced by the three methods so the wind speed distribution functions need to beexamined in order to make an informed choice for dose reconstruction.

    Keywords: dose assessment, meteorology, wind roses

    1. Introduction

    A study of the uncertainties of radioiodine dosimetry from the late 1950s providesthe underlying motivation for developing historical windroses at the SavannahRiver Site (SRS). The larger study examines parameter variability and model sens-itivity in all aspects of internal dosimetry of iodine-131, including atmosphericdispersion and transport, ingestion and inhalation, thyroid uptake, and iodine meta-

    Environmental Monitoring and Assessment 83: 255281, 2003. 2003 Kluwer Academic Publishers. Printed in the Netherlands.

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    bolism in humans. Historical meteorological variables are used in estimating down-wind concentrations of radioiodine in the air, on the ground, and in consumables.A general uncertainty analysis of the Gaussian dispersion model and its sensitivityto joint-frequency inputs has been conducted separately (Hamby, 2002).

    For modeling purposes, it is desirable to utilize meteorological data from thechosen time period. However, prior to this work meteorological data for the Sa-vannah River Site (SRS) did not exist for the 1950s. The Savannah River Sitesmeteorological monitoring program (Parker and Addis, 1993) was not establisheduntil the early 1970s. The focus of the present study is to develop wind data forthe SRS between 1955 and 1961 to be used in an assessment of estimates of atmo-spheric dispersion and downwind risk at the Savannah River Site. With unlimitedresources and under ideal circumstances, very explicit modeling techniques couldbe used to reconstruct historical meteorological data. However, when resources arelimited, other approaches to a reconstruction of winds must be evaluated.

    Efforts to create historical meteorological data can be rather complex and timeconsuming. Kraig (1997) describes dose reconstruction work performed at LosAlamos for weapons experiments from the mid-1940s to early 1960s. Lack ofmeteorological data during many of the tests required Kraig to use averaged con-ditions for the late-afternoon and early-evening time frame (when the tests wereconducted) from a 3 yr database of observations using a single tower located nearthe detonations.

    The meteorology used for the Hanford dose reconstruction effort (mid to late-1940s) is described in Stage et al. (1993). Details are given regarding station in-fluences by local topography, limitations of the data-collection methods, as wellas difficulties in transferring data from original handwritten records or microficheinto a usable database of dose modeling activities.

    When meteorological data are sparse either spatially or temporally, an approachis to use sophisticated atmospheric models initialized with observations from sur-face stations and weather balloons. These models can then create hourly observa-tions over large spatial grids. This implies re-running complex three-dimensionalmesoscale or large-scale models to generate winds over entire years or decadesand results in time-consuming computations (that do not necessarily provide moreaccurate results).

    In the case of the SRS, however, the reasonably close proximity of two NationalWeather Service (NWS) stations enabled the creation of an historical databaseusing three different approaches that are described here. Wind speed and winddirection estimates were obtained by finding mean differences between SRS andNWS stations during the 1990s and creating a set of corrections that were assumedto hold for the 1950s. In a regression approach, statistical regression relationshipsbetween recent SRS and NWS databases for wind speed were determined andapplied to archived NWS data to produce an SRS database for the desired timeperiod. A third approach based on similarity theory was also used to generate windspeeds for the 1950s. In the similarity theory approach, wind speeds from the 10 m


    NWS observations were extended to SRSs 61 m level (under an assumption ofhorizontal spatial homogeneity).

    2. Methods


    The locations of the wind measurement sites, terrain elevations for the region, andsome land-use features are shown in Figure 1. The land use in the South CarolinaPiedmont is primarily agricultural broken by streams, forests and several smallcommunities. The larger cities of Columbia, South Carolina, and Augusta, Georgiaare separated by a distance of about 90 km.

    Wind measurements are taken at the SRS and the NWS sites near the ColumbiaMetropolitan Airport (CAE) and the Augusta Regional Airport at Bush Field (AGS).Although Columbia is roughly twice as far from the SRS as Augusta, the terrainsurrounding the CAE measurement site is more similar to the SRS than the terrainaround AGS. The main difference is that Bush Field lies in the Savannah Riverdrainage basin near swampy terrain. Calms and fog occurrences are much morefrequent at AGS than at CAE or at the SRS.

    Wind measurements at the SRS and the NWS stations have important differ-ences that are summarized in Table I. Perhaps most important is that the meas-urement height at the SRS is 61 m above ground level (AGL), while the NWSstations now typically measure winds at 10 m AGL. In the 1950s through the mid-1960s the wind speed measurement heights were not necessarily at 10 m AGL.According to the National Oceanic and Atmospheric Administrations (NOAA)records of the history of the two sites (NOAA, 1996), the anemometer and windvane were lowered 4.9 m (16 ft) from their height of 11.0 m (36 ft) in 1951 to 6.1 m(20 ft) in the period 19921996 at Columbia (CAE). The same source shows thatAugustas wind instruments were lowered 1.5 m (5 ft) from their height of 7.6 m(25 ft) in 1951 to 6.1 m (20 ft) in the period 19921996. Since wind speed changesapproximately logarithmically with height these rather modest changes in elevationshould have affected the speeds by no more than about 515%. In addition, theNWS instruments are much less sensitive than the SRS instrumentation, and theBush Field data are subject to down-river flow due to the airports geographicallocation (Figure 1). Finally, the NWS values are 1 or 2 min averages at the top ofthe hour (i.e. almost a snapshot), whereas the SRS data are averaged continuouslyover one-hour intervals.

    The SRS wind speed and direction measurements for this project were takenfrom a 61 m tower in H-Area near the center of the SRS. A five-year databasefor the period 19921996 was assembled for dosimetry calculations and this samedatabase was used here. The SRS 19921996 database underwent several qualityassurance procedures prior to being finalized. One of the requirements for the do-simetry calculations was that the meteorological data had to be complete for each

  • 258 A. H. WEBER ET AL.

    Figure 1. Map of the Savannah River Site (SRS) area with Augusta Bush Field (AGS) to the northwestand Columbia airport (CAE) in the northeast corner. Topographic contours are at 25 m (above sealevel) intervals with 50 and 100 m levels highlighted. Lighter shaded filled areas are cities or towns.

    hour of the five-year period. This requirement was possible to meet since SRS hasseven 61 m towers, and whenever the data from the H-Area tower was missing, thewind speed and/or direction could be substituted from one of the remaining towers.

    The first step in developing the desired statistical relationships was to obtainNWSs meteorological data from the National Climatic Data Center (NCDC) (Earth-Info, 1996; Brown, 2001) for all nearby NWS stations in the region and to examineeach station for appropriateness. In addition to AGS and CAE these stations in-cluded Athens and Macon, Georgia; Charlotte, North Carolina; and Charleston,South Carolina. Hourly observations of wind speed, direction, cloud cover, andcloud-height from Bush Field in Augusta, Georgia (AGS) and Columbia, SouthCarolina (CAE) from 19551961 and 19921996 were selected after an initialscreening to reconstruct the winds at the SRS. The other stations in the region were


    Known difference between the winds measured at the National Weather Service, Augusta, Georgia(AGS) Columbia, South Carolina (CAE) and the Savannah River Site (SRS)

    Difference SRS CAE AGS

    Height of sensors 61 m 11.0 to 6.1 m 7.6 to 6.1 m(1951 to 19921996) (1951 to 19921996)

    Instrument High sensitivity Robust instrumentation, Robust instrumentation,sensitivity but low sensitivity. but low sensitivity.

    Averaging time 1 hr (continuous) 2 min (snap-shot) 2 min (snap-shot)Topographical Pine tree forest. Airport location. Airport location.influences Mostly flat within Lies near partially Lies at the edge of

    2.0 km of the tower. developed suburban the Savannah RiverModest terrain landscape. drainage basin.changes beyond.

    rejected for various reasons, such as displaying orographic effects or for exhibitingclimatologically different conditions than the SRS.

    The wind speed frequency distributions for 19921996 for SRS and the twoselected NWS sites are shown in Figures 2ac. As mentioned above, the SRSwind speed data in Figure 2 were taken at the 61 m height with highly sensitiveanemometers. The distribution resembles the theoretical Weibull distribution witha shape parameter of 2 that is expected for accurate, continuous, long-term windmeasurements (Krohn 1997). (Wind speed units of knots (kt) were used in thefigures since the NCDC values are reported in whole knots).

    The AGS and CAE frequency distributions, however, show spikes near zeroreflecting the large number of wind speeds below the threshold of the NWS an-emometer (recorded as a missing direction and a zero for wind speed). Indeed,an examination of the data showed that for the entire period 19921996, virtuallyall the wind speeds below 1.54 m s1 (3 kt) were entered as zeros for the NWSstations.

    To make the NWS distributions appear more realistic, a method was developedto create more representative looking wind speed distributions. Zero wind speedvalues were reassigned a random speed between zero and 1.54 m s1 (3 kt) asfollows: values between 1.03 and 1.54 m s1 (2 and 3 knots) were assigned threetimes as frequently as values between zero and 0.257 m s1 (0.5 knots), and valuesbetween 0.257 and 1.03 m s1 (0.5 and 2 knots) were assigned twice as frequentlyas values between zero and 0.257 m s1 (zero and 0.5 knots).

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    Figure 2a-c. Wind speed frequency distributions for 19921996 for (a) SRS and (b) CAE. Windspeed units of knots are used for clarity since the NWS reports wind speed to the nearest knot.


    Figure 2c. Wind speed frequency distributions for 19921996 for AGS. Wind speed units of knotsare used for clarity since the NWS reports wind speed to the nearest knot.

    The modified NWS wind speed distributions for the two sites are shown inFigures 3ab. The resulting CAE distribution appears reasonable, resembling atruncated Weibull distribution; the AGS distribution looks questionable with twomaxima below 2.57 m s1 (5 kt), as though too many winds had been recordedas calm. Since the shape of CAEs modified wind speed distribution function inFigure 3 appeared to more closely resemble the SRS distribution in Figure 2 thandid the AGS distribution, the CAE wind speed data were given preference in thedata reconstruction for SRS.

    It was also determined that a significant percentage of the Bush Field winddirection data were missing for the periods of interest (including the 1990s). Thiswas mainly due to calm winds being reported, since Bush Field lies in the SavannahRiver drainage basin. The wind measurements at CAE had the advantage of beingmore complete as well as being collected over terrain more similar to the SRS thanthe AGS site, so CAE was given preference to represent wind directions for theSRS for the 1950s. To improve the percentage of direction data recovered for CAEif data were missing for 1, 2 hr, etc., or longer segments up to 8 hr, then persistencefrom the last known non-missing value was utilized. Performing these substitutionsresulted in a gain of 17% so that missing direction data were reduced to onlyabout 0.5% in the final data set.

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    Figure 3a-b. Modified wind speed frequency distributions for 19921996 for (a) CAE, (b) AGS.Modifications were performed on the c...


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