| 1 | !> |
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| 2 | !! |
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| 3 | !! @brief Module MO_SIMPLE_PLUMES: provides anthropogenic aerosol optical properties as a function of lat, lon |
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| 4 | !! height, time, and wavelength |
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| 5 | !! |
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| 6 | !! @remarks |
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| 7 | !! |
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| 8 | !! @author Bjorn Stevens, Stephanie Fiedler and Karsten Peters MPI-Met, Hamburg (v1 release 2016-11-10) |
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| 9 | !! |
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| 10 | !! @change-log: |
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| 11 | !! - 2016-12-05: beta release (BS, SF and KP, MPI-Met) |
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| 12 | !! - 2016-09-28: revised representation of Twomey effect (SF, MPI-Met) |
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| 13 | !! - 2015-09-28: bug fixes (SF, MPI-Met) |
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| 14 | !! - 2016-10-12: revised maximum longitudinal extent of European plume (KP, SF, MPI-Met) |
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| 15 | !! $ID: n/a$ |
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| 16 | !! |
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| 17 | !! @par Origin |
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| 18 | !! Based on code originally developed at the MPI-Met by Karsten Peters, Bjorn Stevens, Stephanie Fiedler |
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| 19 | !! and Stefan Kinne with input from Thorsten Mauritsen and Robert Pincus |
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| 20 | !! |
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| 21 | !! @par Copyright |
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| 22 | !! |
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| 23 | ! |
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| 24 | MODULE MO_SIMPLE_PLUMES |
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| 25 | |
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| 26 | USE netcdf |
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| 27 | |
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| 28 | IMPLICIT NONE |
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| 29 | |
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| 30 | INTEGER, PARAMETER :: & |
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| 31 | nplumes = 9 ,& !< Number of plumes |
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| 32 | nfeatures = 2 ,& !< Number of features per plume |
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| 33 | ntimes = 52 ,& !< Number of times resolved per year (52 => weekly resolution) |
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| 34 | nyears = 251 !< Number of years of available forcing |
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| 35 | |
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| 36 | LOGICAL, SAVE :: & |
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| 37 | sp_initialized = .FALSE. !< parameter determining whether input needs to be read |
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| 38 | |
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| 39 | REAL :: & |
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| 40 | plume_lat (nplumes) ,& !< latitude of plume center (AOD maximum) |
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| 41 | plume_lon (nplumes) ,& !< longitude of plume center (AOD maximum) |
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| 42 | beta_a (nplumes) ,& !< parameter a for beta function vertical profile |
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| 43 | beta_b (nplumes) ,& !< parameter b for beta function vertical profile |
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| 44 | aod_spmx (nplumes) ,& !< anthropogenic AOD maximum at 550 for plumes |
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| 45 | aod_fmbg (nplumes) ,& !< anthropogenic AOD at 550 for fine-mode natural background (idealized to mimic Twomey effect) |
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| 46 | asy550 (nplumes) ,& !< asymmetry parameter at 550nm for plume |
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| 47 | ssa550 (nplumes) ,& !< single scattering albedo at 550nm for plume |
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| 48 | angstrom (nplumes) ,& !< Angstrom parameter for plume |
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| 49 | sig_lon_E (nfeatures,nplumes) ,& !< Eastward extent of plume feature |
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| 50 | sig_lon_W (nfeatures,nplumes) ,& !< Westward extent of plume feature |
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| 51 | sig_lat_E (nfeatures,nplumes) ,& !< Southward extent of plume feature |
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| 52 | sig_lat_W (nfeatures,nplumes) ,& !< Northward extent of plume feature |
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| 53 | theta (nfeatures,nplumes) ,& !< Rotation angle of plume feature |
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| 54 | ftr_weight (nfeatures,nplumes) ,& !< Feature weights |
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| 55 | time_weight (nfeatures,nplumes) ,& !< Time weights |
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| 56 | time_weight_bg (nfeatures,nplumes) ,& !< as time_weight but for natural background in Twomey effect |
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| 57 | year_weight (nyears,nplumes) ,& !< Yearly weight for plume |
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| 58 | ann_cycle (nfeatures,ntimes,nplumes) !< annual cycle for plume feature |
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| 59 | |
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| 60 | PUBLIC sp_aop_profile |
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| 61 | |
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| 62 | CONTAINS |
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| 63 | ! |
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| 64 | ! ------------------------------------------------------------------------------------------------------------------------ |
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| 65 | ! SP_SETUP: This subroutine should be called at initialization to read the netcdf data that describes the simple plume |
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| 66 | ! climatology. The information needs to be either read by each processor or distributed to processors. |
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| 67 | ! |
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| 68 | SUBROUTINE sp_setup |
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| 69 | ! |
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| 70 | ! ---------- |
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| 71 | ! |
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| 72 | INTEGER :: iret, ncid, DimID, VarID, xdmy |
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| 73 | ! |
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| 74 | ! ---------- |
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| 75 | ! |
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| 76 | iret = nf90_open("MACv2.0-SP_v1.nc", NF90_NOWRITE, ncid) |
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| 77 | IF (iret /= NF90_NOERR) STOP 'NetCDF File not opened' |
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| 78 | ! |
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| 79 | ! read dimensions and make sure file conforms to expected size |
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| 80 | ! |
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| 81 | iret = nf90_inq_dimid(ncid, "plume_number" , DimId) |
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| 82 | iret = nf90_inquire_dimension(ncid, DimId, len = xdmy) |
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| 83 | IF (xdmy /= nplumes) STOP 'NetCDF improperly dimensioned -- plume_number' |
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| 84 | |
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| 85 | iret = nf90_inq_dimid(ncid, "plume_feature", DimId) |
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| 86 | iret = nf90_inquire_dimension(ncid, DimId, len = xdmy) |
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| 87 | IF (xdmy /= nfeatures) STOP 'NetCDF improperly dimensioned -- plume_feature' |
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| 88 | |
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| 89 | iret = nf90_inq_dimid(ncid, "year_fr" , DimId) |
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| 90 | iret = nf90_inquire_dimension(ncid, DimID, len = xdmy) |
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| 91 | IF (xdmy /= ntimes) STOP 'NetCDF improperly dimensioned -- year_fr' |
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| 92 | |
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| 93 | iret = nf90_inq_dimid(ncid, "years" , DimId) |
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| 94 | iret = nf90_inquire_dimension(ncid, DimID, len = xdmy) |
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| 95 | IF (xdmy /= nyears) STOP 'NetCDF improperly dimensioned -- years' |
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| 96 | ! |
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| 97 | ! read variables that define the simple plume climatology |
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| 98 | ! |
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| 99 | iret = nf90_inq_varid(ncid, "plume_lat", VarId) |
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| 100 | iret = nf90_get_var(ncid, VarID, plume_lat(:), start=(/1/),count=(/nplumes/)) |
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| 101 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading plume_lat' |
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| 102 | iret = nf90_inq_varid(ncid, "plume_lon", VarId) |
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| 103 | iret = nf90_get_var(ncid, VarID, plume_lon(:), start=(/1/),count=(/nplumes/)) |
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| 104 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading plume_lon' |
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| 105 | iret = nf90_inq_varid(ncid, "beta_a" , VarId) |
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| 106 | iret = nf90_get_var(ncid, VarID, beta_a(:) , start=(/1/),count=(/nplumes/)) |
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| 107 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading beta_a' |
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| 108 | iret = nf90_inq_varid(ncid, "beta_b" , VarId) |
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| 109 | iret = nf90_get_var(ncid, VarID, beta_b(:) , start=(/1/),count=(/nplumes/)) |
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| 110 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading beta_b' |
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| 111 | iret = nf90_inq_varid(ncid, "aod_spmx" , VarId) |
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| 112 | iret = nf90_get_var(ncid, VarID, aod_spmx(:) , start=(/1/),count=(/nplumes/)) |
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| 113 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading aod_spmx' |
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| 114 | iret = nf90_inq_varid(ncid, "aod_fmbg" , VarId) |
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| 115 | iret = nf90_get_var(ncid, VarID, aod_fmbg(:) , start=(/1/),count=(/nplumes/)) |
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| 116 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading aod_fmbg' |
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| 117 | iret = nf90_inq_varid(ncid, "ssa550" , VarId) |
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| 118 | iret = nf90_get_var(ncid, VarID, ssa550(:) , start=(/1/),count=(/nplumes/)) |
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| 119 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading ssa550' |
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| 120 | iret = nf90_inq_varid(ncid, "asy550" , VarId) |
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| 121 | iret = nf90_get_var(ncid, VarID, asy550(:) , start=(/1/),count=(/nplumes/)) |
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| 122 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading asy550' |
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| 123 | iret = nf90_inq_varid(ncid, "angstrom" , VarId) |
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| 124 | iret = nf90_get_var(ncid, VarID, angstrom(:), start=(/1/),count=(/nplumes/)) |
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| 125 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading angstrom' |
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| 126 | |
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| 127 | iret = nf90_inq_varid(ncid, "sig_lat_W" , VarId) |
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| 128 | iret = nf90_get_var(ncid, VarID, sig_lat_W(:,:) , start=(/1,1/),count=(/nfeatures,nplumes/)) |
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| 129 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading sig_lat_W' |
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| 130 | iret = nf90_inq_varid(ncid, "sig_lat_E" , VarId) |
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| 131 | iret = nf90_get_var(ncid, VarID, sig_lat_E(:,:) , start=(/1,1/),count=(/nfeatures,nplumes/)) |
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| 132 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading sig_lat_E' |
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| 133 | iret = nf90_inq_varid(ncid, "sig_lon_E" , VarId) |
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| 134 | iret = nf90_get_var(ncid, VarID, sig_lon_E(:,:) , start=(/1,1/),count=(/nfeatures,nplumes/)) |
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| 135 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading sig_lon_E' |
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| 136 | iret = nf90_inq_varid(ncid, "sig_lon_W" , VarId) |
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| 137 | iret = nf90_get_var(ncid, VarID, sig_lon_W(:,:) , start=(/1,1/),count=(/nfeatures,nplumes/)) |
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| 138 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading sig_lon_W' |
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| 139 | iret = nf90_inq_varid(ncid, "theta" , VarId) |
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| 140 | iret = nf90_get_var(ncid, VarID, theta(:,:) , start=(/1,1/),count=(/nfeatures,nplumes/)) |
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| 141 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading theta' |
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| 142 | iret = nf90_inq_varid(ncid, "ftr_weight" , VarId) |
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| 143 | iret = nf90_get_var(ncid, VarID, ftr_weight(:,:) , start=(/1,1/),count=(/nfeatures,nplumes/)) |
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| 144 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading plume_lat' |
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| 145 | iret = nf90_inq_varid(ncid, "year_weight" , VarId) |
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| 146 | iret = nf90_get_var(ncid, VarID, year_weight(:,:) , start=(/1,1/),count=(/nyears,nplumes /)) |
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| 147 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading year_weight' |
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| 148 | iret = nf90_inq_varid(ncid, "ann_cycle" , VarId) |
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| 149 | iret = nf90_get_var(ncid, VarID, ann_cycle(:,:,:) , start=(/1,1,1/),count=(/nfeatures,ntimes,nplumes/)) |
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| 150 | IF (iret /= NF90_NOERR) STOP 'NetCDF Error reading ann_cycle' |
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| 151 | |
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| 152 | iret = nf90_close(ncid) |
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| 153 | |
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| 154 | sp_initialized = .TRUE. |
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| 155 | |
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| 156 | RETURN |
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| 157 | END SUBROUTINE sp_setup |
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| 158 | ! |
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| 159 | ! ------------------------------------------------------------------------------------------------------------------------ |
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| 160 | ! SET_TIME_WEIGHT: The simple plume model assumes that meteorology constrains plume shape and that only source strength |
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| 161 | ! influences the amplitude of a plume associated with a given source region. This routine retrieves the temporal weights |
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| 162 | ! for the plumes. Each plume feature has its own temporal weights which varies yearly. The annual cycle is indexed by |
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| 163 | ! week in the year and superimposed on the yearly mean value of the weight. |
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| 164 | ! |
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| 165 | SUBROUTINE set_time_weight(year_fr) |
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| 166 | ! |
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| 167 | ! ---------- |
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| 168 | ! |
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| 169 | REAL, INTENT(IN) :: & |
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| 170 | year_fr !< Fractional Year (1850.0 - 2100.99) |
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| 171 | |
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| 172 | INTEGER :: & |
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| 173 | iyear ,& !< Integer year values between 1 and 156 (1850-2100) |
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| 174 | iweek ,& !< Integer index (between 1 and ntimes); for ntimes=52 this corresponds to weeks (roughly) |
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| 175 | iplume ! plume number |
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| 176 | ! |
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| 177 | ! ---------- |
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| 178 | ! |
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| 179 | iyear = FLOOR(year_fr) - 1849 |
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| 180 | iweek = FLOOR((year_fr - FLOOR(year_fr)) * ntimes) + 1 |
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| 181 | |
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| 182 | IF ((iweek > ntimes) .OR. (iweek < 1) .OR. (iyear > nyears) .OR. (iyear < 1)) THEN |
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| 183 | CALL abort_physic('set_time_weight','Time out of bounds') |
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| 184 | ENDIF |
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| 185 | |
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| 186 | DO iplume=1,nplumes |
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| 187 | time_weight(1,iplume) = year_weight(iyear,iplume) * ann_cycle(1,iweek,iplume) |
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| 188 | time_weight(2,iplume) = year_weight(iyear,iplume) * ann_cycle(2,iweek,iplume) |
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| 189 | time_weight_bg(1,iplume) = ann_cycle(1,iweek,iplume) |
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| 190 | time_weight_bg(2,iplume) = ann_cycle(2,iweek,iplume) |
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| 191 | END DO |
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| 192 | |
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| 193 | RETURN |
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| 194 | END SUBROUTINE set_time_weight |
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| 195 | ! |
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| 196 | ! ------------------------------------------------------------------------------------------------------------------------ |
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| 197 | ! SP_AOP_PROFILE: This subroutine calculates the simple plume aerosol and cloud active optical properties based on the |
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| 198 | ! the simple plume fit to the MPI Aerosol Climatology (Version 2). It sums over nplumes to provide a profile of aerosol |
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| 199 | ! optical properties on a host models vertical grid. |
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| 200 | ! |
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| 201 | SUBROUTINE sp_aop_profile ( & |
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| 202 | nlevels ,ncol ,lambda ,oro ,lon ,lat , & |
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| 203 | year_fr ,z ,dz ,dNovrN ,aod_prof ,ssa_prof , & |
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| 204 | asy_prof ) |
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| 205 | ! |
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| 206 | ! ---------- |
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| 207 | ! |
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| 208 | INTEGER, INTENT(IN) :: & |
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| 209 | nlevels, & !< number of levels |
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| 210 | ncol !< number of columns |
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| 211 | |
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| 212 | REAL, INTENT(IN) :: & |
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| 213 | lambda, & !< wavelength |
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| 214 | year_fr, & !< Fractional Year (1903.0 is the 0Z on the first of January 1903, Gregorian) |
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| 215 | oro(ncol), & !< orographic height (m) |
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| 216 | lon(ncol), & !< longitude |
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| 217 | lat(ncol), & !< latitude |
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| 218 | z (ncol,nlevels), & !< height above sea-level (m) |
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| 219 | dz(ncol,nlevels) !< level thickness (difference between half levels) (m) |
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| 220 | |
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| 221 | REAL, INTENT(OUT) :: & |
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| 222 | dNovrN(ncol) , & !< anthropogenic increase in cloud drop number concentration (factor) |
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| 223 | aod_prof(ncol,nlevels) , & !< profile of aerosol optical depth |
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| 224 | ssa_prof(ncol,nlevels) , & !< profile of single scattering albedo |
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| 225 | asy_prof(ncol,nlevels) !< profile of asymmetry parameter |
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| 226 | |
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| 227 | INTEGER :: iplume, icol, k |
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| 228 | |
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| 229 | REAL :: & |
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| 230 | eta(ncol,nlevels), & !< normalized height (by 15 km) |
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| 231 | z_beta(ncol,nlevels), & !< profile for scaling column optical depth |
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| 232 | prof(ncol,nlevels), & !< scaled profile (by beta function) |
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| 233 | beta_sum(ncol), & !< vertical sum of beta function |
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| 234 | ssa(ncol), & !< single scattering albedo |
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| 235 | asy(ncol), & !< asymmetry parameter |
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| 236 | cw_an(ncol), & !< column weight for simple plume (anthropogenic) AOD at 550 nm |
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| 237 | cw_bg(ncol), & !< column weight for fine-mode natural background AOD at 550 nm |
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| 238 | caod_sp(ncol), & !< column simple plume anthropogenic AOD at 550 nm |
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| 239 | caod_bg(ncol), & !< column fine-mode natural background AOD at 550 nm |
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| 240 | a_plume1, & !< gaussian longitude factor for feature 1 |
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| 241 | a_plume2, & !< gaussian longitude factor for feature 2 |
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| 242 | b_plume1, & !< gaussian latitude factor for feature 1 |
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| 243 | b_plume2, & !< gaussian latitude factor for feature 2 |
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| 244 | delta_lat, & !< latitude offset |
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| 245 | delta_lon, & !< longitude offset |
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| 246 | delta_lon_t, & !< threshold for maximum longitudinal plume extent used in transition from 360 to 0 degrees |
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| 247 | lon1, & !< rotated longitude for feature 1 |
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| 248 | lat1, & !< rotated latitude for feature 2 |
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| 249 | lon2, & !< rotated longitude for feature 1 |
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| 250 | lat2, & !< rotated latitude for feature 2 |
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| 251 | f1, & !< contribution from feature 1 |
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| 252 | f2, & !< contribution from feature 2 |
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| 253 | f3, & !< contribution from feature 1 in natural background of Twomey effect |
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| 254 | f4, & !< contribution from feature 2 in natural background of Twomey effect |
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| 255 | aod_550, & !< aerosol optical depth at 550nm |
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| 256 | aod_lmd, & !< aerosol optical depth at input wavelength |
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| 257 | lfactor !< factor to compute wavelength dependence of optical properties |
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| 258 | ! |
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| 259 | ! ---------- |
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| 260 | ! |
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| 261 | ! initialize input data (by calling setup at first instance) |
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| 262 | ! |
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| 263 | IF (.NOT.sp_initialized) CALL sp_setup |
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| 264 | ! |
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| 265 | ! get time weights |
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| 266 | ! |
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| 267 | CALL set_time_weight(year_fr) |
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| 268 | ! |
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| 269 | ! initialize variables, including output |
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| 270 | ! |
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| 271 | DO k=1,nlevels |
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| 272 | DO icol=1,ncol |
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| 273 | aod_prof(icol,k) = 0.0 |
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| 274 | ssa_prof(icol,k) = 0.0 |
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| 275 | asy_prof(icol,k) = 0.0 |
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| 276 | z_beta(icol,k) = MERGE(1.0, 0.0, z(icol,k) >= oro(icol)) |
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| 277 | eta(icol,k) = MAX(0.0,MIN(1.0,z(icol,k)/15000.)) |
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| 278 | END DO |
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| 279 | END DO |
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| 280 | DO icol=1,ncol |
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| 281 | dNovrN(icol) = 1.0 |
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| 282 | caod_sp(icol) = 0.0 |
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| 283 | caod_bg(icol) = 0.02 |
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| 284 | END DO |
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| 285 | ! |
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| 286 | ! sum contribution from plumes to construct composite profiles of aerosol optical properties |
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| 287 | ! |
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| 288 | DO iplume=1,nplumes |
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| 289 | ! |
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| 290 | ! calculate vertical distribution function from parameters of beta distribution |
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| 291 | ! |
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| 292 | DO icol=1,ncol |
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| 293 | beta_sum(icol) = 0. |
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| 294 | END DO |
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| 295 | DO k=1,nlevels |
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| 296 | DO icol=1,ncol |
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| 297 | prof(icol,k) = (eta(icol,k)**(beta_a(iplume)-1.) * (1.-eta(icol,k))**(beta_b(iplume)-1.)) * dz(icol,k) |
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| 298 | beta_sum(icol) = beta_sum(icol) + prof(icol,k) |
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| 299 | END DO |
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| 300 | END DO |
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| 301 | DO k=1,nlevels |
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| 302 | DO icol=1,ncol |
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| 303 | prof(icol,k) = ( prof(icol,k) / beta_sum(icol) ) * z_beta(icol,k) |
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| 304 | END DO |
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| 305 | END DO |
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| 306 | ! |
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| 307 | ! calculate plume weights |
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| 308 | ! |
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| 309 | DO icol=1,ncol |
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| 310 | ! |
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| 311 | ! get plume-center relative spatial parameters for specifying amplitude of plume at given lat and lon |
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| 312 | ! |
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| 313 | delta_lat = lat(icol) - plume_lat(iplume) |
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| 314 | delta_lon = lon(icol) - plume_lon(iplume) |
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| 315 | delta_lon_t = MERGE (260., 180., iplume == 1) |
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| 316 | delta_lon = MERGE ( delta_lon-SIGN(360.,delta_lon) , delta_lon , ABS(delta_lon) > delta_lon_t) |
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| 317 | |
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| 318 | a_plume1 = 0.5 / (MERGE(sig_lon_E(1,iplume), sig_lon_W(1,iplume), delta_lon > 0)**2) |
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| 319 | b_plume1 = 0.5 / (MERGE(sig_lat_E(1,iplume), sig_lat_W(1,iplume), delta_lon > 0)**2) |
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| 320 | a_plume2 = 0.5 / (MERGE(sig_lon_E(2,iplume), sig_lon_W(2,iplume), delta_lon > 0)**2) |
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| 321 | b_plume2 = 0.5 / (MERGE(sig_lat_E(2,iplume), sig_lat_W(2,iplume), delta_lon > 0)**2) |
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| 322 | ! |
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| 323 | ! adjust for a plume specific rotation which helps match plume state to climatology. |
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| 324 | ! |
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| 325 | lon1 = COS(theta(1,iplume))*(delta_lon) + SIN(theta(1,iplume))*(delta_lat) |
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| 326 | lat1 = - SIN(theta(1,iplume))*(delta_lon) + COS(theta(1,iplume))*(delta_lat) |
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| 327 | lon2 = COS(theta(2,iplume))*(delta_lon) + SIN(theta(2,iplume))*(delta_lat) |
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| 328 | lat2 = - SIN(theta(2,iplume))*(delta_lon) + COS(theta(2,iplume))*(delta_lat) |
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| 329 | ! |
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| 330 | ! calculate contribution to plume from its different features, to get a column weight for the anthropogenic |
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| 331 | ! (cw_an) and the fine-mode natural background aerosol (cw_bg) |
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| 332 | ! |
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| 333 | f1 = time_weight(1,iplume) * ftr_weight(1,iplume) * EXP(-1.* (a_plume1 * ((lon1)**2) + (b_plume1 * ((lat1)**2)))) |
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| 334 | f2 = time_weight(2,iplume) * ftr_weight(2,iplume) * EXP(-1.* (a_plume2 * ((lon2)**2) + (b_plume2 * ((lat2)**2)))) |
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| 335 | f3 = time_weight_bg(1,iplume) * ftr_weight(1,iplume) * EXP(-1.* (a_plume1 * ((lon1)**2) + (b_plume1 * ((lat1)**2)))) |
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| 336 | f4 = time_weight_bg(2,iplume) * ftr_weight(2,iplume) * EXP(-1.* (a_plume2 * ((lon2)**2) + (b_plume2 * ((lat2)**2)))) |
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| 337 | |
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| 338 | cw_an(icol) = f1 * aod_spmx(iplume) + f2 * aod_spmx(iplume) |
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| 339 | cw_bg(icol) = f3 * aod_fmbg(iplume) + f4 * aod_fmbg(iplume) |
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| 340 | ! |
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| 341 | ! calculate wavelength-dependent scattering properties |
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| 342 | ! |
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| 343 | lfactor = MIN(1.0,700.0/lambda) |
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| 344 | ssa(icol) = (ssa550(iplume) * lfactor**4) / ((ssa550(iplume) * lfactor**4) + ((1-ssa550(iplume)) * lfactor)) |
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| 345 | asy(icol) = asy550(iplume) * SQRT(lfactor) |
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| 346 | END DO |
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| 347 | ! |
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| 348 | ! distribute plume optical properties across its vertical profile weighting by optical depth and scaling for |
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| 349 | ! wavelength using the angstrom parameter. |
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| 350 | ! |
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| 351 | lfactor = EXP(-angstrom(iplume) * LOG(lambda/550.0)) |
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| 352 | DO k=1,nlevels |
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| 353 | DO icol = 1,ncol |
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| 354 | aod_550 = prof(icol,k) * cw_an(icol) |
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| 355 | aod_lmd = aod_550 * lfactor |
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| 356 | caod_sp(icol) = caod_sp(icol) + aod_550 |
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| 357 | caod_bg(icol) = caod_bg(icol) + prof(icol,k) * cw_bg(icol) |
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| 358 | asy_prof(icol,k) = asy_prof(icol,k) + aod_lmd * ssa(icol) * asy(icol) |
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| 359 | ssa_prof(icol,k) = ssa_prof(icol,k) + aod_lmd * ssa(icol) |
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| 360 | aod_prof(icol,k) = aod_prof(icol,k) + aod_lmd |
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| 361 | END DO |
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| 362 | END DO |
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| 363 | END DO |
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| 364 | ! |
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| 365 | ! complete optical depth weighting |
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| 366 | ! |
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| 367 | DO k=1,nlevels |
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| 368 | DO icol = 1,ncol |
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| 369 | asy_prof(icol,k) = MERGE(asy_prof(icol,k)/ssa_prof(icol,k), 0.0, ssa_prof(icol,k) > TINY(1.)) |
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| 370 | ssa_prof(icol,k) = MERGE(ssa_prof(icol,k)/aod_prof(icol,k), 1.0, aod_prof(icol,k) > TINY(1.)) |
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| 371 | END DO |
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| 372 | END DO |
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| 373 | ! |
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| 374 | ! calculate effective radius normalization (divisor) factor |
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| 375 | ! |
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| 376 | DO icol=1,ncol |
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| 377 | dNovrN(icol) = LOG((1000.0 * (caod_sp(icol) + caod_bg(icol))) + 1.0)/LOG((1000.0 * caod_bg(icol)) + 1.0) |
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| 378 | END DO |
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| 379 | |
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| 380 | RETURN |
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| 381 | END SUBROUTINE sp_aop_profile |
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| 382 | |
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| 383 | END MODULE MO_SIMPLE_PLUMES |
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