284 Health Physics at the two successive particle positions, mtegratmg over the duration of the time-step, and then adding the displacement to the imtial position of the particle The imtegration time-step can vary from | to 60 min but 1s bound by a user-specified advection distance per trmestep to limit the advectionto less than one grid pomt per time-step Dispersion 1s computedafter the advection compu- tation, however, 1t 18 necessary for the model to first compute stability and mixing coefficients Stabihty and mixing are estrmated from the meteorological input data Heat and momentum fluxes, 1f they are present m the meteorological data, are used to compute the stability, otherwise temperature and wind data at each grid pomt are used to estimate it Vertical mixmg withm the boundary layer 1s computed as an average at each horizontal grid pomt based upon flux data Above the boundary layer, vertical mixmg 1s estimated from the wind and temperature profiles Horizontal mixmg 1s computed usmg the deformations m the wid field and 1s adjusted based on the size of the meteorological grid Toreahstically simulate the dispersive nature of the atmosphere, a random turbulent component 1s mcorporated mto the dispersion calculation by adding the turbulent component to the mean velocity obtamed from the meteorological mput data at each trme-step This turbulent component 1s a Gaussian based pseudo-randomly generated number resultmg from the product of the Gaussian random number and the standard deviation of the computed turbulent velocity of the velocity vector (Draxler and Hess 1997) The Gaussian random number is generated usmg a variation of the lmear congruential method, X,,, = (aX, + c) mod m, where the element 1 indicates the position of the random number withm the sequence When the parameters a, c, and m are chosen correctly, generatorsofthis class can ensure a nonrepeating sequence on thescale of 10° It should be noted that though the HYSPLIT model mcorporates a random turbulence element, the model 1s not stochastic because the same random sequence1s generated with each mvo- cation of the model, meanmg that the model results for any single simulation will always be the same assuming the simulation parameters are not changed This can be altered by simply modifymg the model’s random number algorithm to apply a different seed value with each mvocation Several dry deposition options are available to the model user In our case, dry deposition was simulated under the assumption that the deposition velocity for all particles was equivalent to the gravitanonal setthng velocity For local fallout from weaponstests, this 1s a reasonable approximation smce most ofthe radioactivity is found on particles of diameter greater than 5 yam August 2010, Volume 99, Number 2 (Heidt et al 1953, Crocker et al 1965, Ibrahim et al 2010) Other HYSPLIT options mclude implicitly specifymg a dry deposition velocity or usmg the resistance method (Draxler and Hess 1997) In our simulations, gravitational setthng was computed by the model based on particle diameter, a fixed particle density of 25 g em”, anda fixed spherical particle shape The computed setthng velocity 1s applied to the vertical position of the particle at each time-step Particles are subject to dry deposition removal processes upon entering the model’s surface layer The model computes dry deposition using one of two options either removing a fraction of the particle’s mass over successive time-steps unti] the mass becomes zero, or computing the probability that a partcle will deposit all of 1ts mass during a single time-step (Draxler and Hess 1997) In our simulations the depost- tion probability option was used Wet deposition processes impose difficulties m meteorological computer models The difficulty stems from the simplified assumptions incorporated ito wet deposition models coupled with a general Jack of rehable precipitation observations m the meteorological mput data (Draxler and Hess 1997) Both m-cloud (ramout) and below-cloud (washout) wet deposition are estimated im the HYSPLIT model by defming thefraction of total pollutant mass within and below the cloud layer and applymg an estimated deposition rate The extent of the cloud layer 1s defmed usmg relative humidity (RH) in the meteorological profile at each horizontal grid point The cloud top and bottom are, by default, defined at 60% and 80% RH, respectively In the case of ramout, a wet deposition velocity 1s calculated as the product of the precipitation rate at the grid pomt anda pollutant-specific scavenging ratio The scavenging ratio 1s based on the amount ofpollutant (g L~') im the arr within the cloud to that m the ram (g L~') measured on the ground atthe grid pomt (Draxler 1999) The wet deposition velocity is then apphedto the fraction of pollutant mass within the cloud layer Below-cloud removal1s defined usmg only rate constant (s~') and 1s mdependent of precrpitation rate (Draxler and Hess 1997) The rate constant 1s applied to the fraction ofpollutant that 1s below the cloud bottom In our simulations, the model’s default values for the tn-cloud scavengmg ratio (32 X 10° L per L) and the below-cloud rate constant (50 X 107° s7') for wet deposition processes were used The total deposition over a time-step 1s the sum of the removal amounts resutmg from each process The total pollutant mass 1s then reduced by the computed removal fraction (Draxler and Hess 1997) Several verification examples demonstrating the apphcability and accuracy of HY SPLIT computations in the areas of particle advection, dispersion, and deposition

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# Predictions of Dispersion and Deposition of Fallout From Nuclear Testing Using the Noaa-Hysplit Meteorological Model (Journal Article Vol. 99, No. 2 August 2010)

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