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LDASsa_DEFAULT_inputs_ensupd.nml
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2371 lines (2249 loc) · 92 KB
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!
! namelist of EnKF inputs for land EnKF update
!
! reichle, 28 Jan 2005
! reichle, 13 Jun 2011 - updated for SMOS angles and downscaling ("FOV")
! reichle, 8 Jun 2017 - added "%flistpath" and "%flistname"; updated comments
! qliu+reichle, 29 Apr 2020 - added forecast error covariance inflation
! qzhang,wjiang,reichle,
! 7 May 2021 - removed "dtstep_assim" and "centered_update"; replaced with MAPL
! resource parameters "LANDASSIM_DT" and "LANDASSIM_T0" (in LDAS.rc)
!
! ----------------------------------------------------------------------
&ens_upd_inputs
! ----------------------------------------------------------------------
!
! update type - for details see subroutine cat_enkf_update()
! (note: all 3d updates use compact support)
!
! local = "1d", regional = "3d"
!
! # = no longer supported
!
! update_type | analysis state vector | assimilated obs
! -------------------------------------------------------------------------------------------------
! 0 | NO assimilation, NO bias correction | n/a
! # 1 | 1d soil moisture | sfmc
! # 2 | 3d soil moisture | sfmc
! 3 | 1d Tskin (assim incr NOT applied, use w/ bias corr) | Tskin
! 4 | 1d Tskin/ght1 (assim incr applied, use w/ or w/o bias corr) | Tskin
! 5 | 1d Tskin/ght1 (assim incr NOT applied, use w/ bias corr) | Tskin
! 6 | 1d soil moisture/Tskin/ght(1) | Tb
! 7 | 3d Tskin/ght1 update | Tskin
! 8 | 3d soil moisture/Tskin/ght(1) | Tb
! 9 | 1d Tskin/ght1 update | FT
! 10 | 3d soil moisture/Tskin/ght(1) excl. catdef unless PEATCLSM tile | Tb
! 11 | 1d snow analysis (Toure et al. 2018 empirical gain) | SCF
! 12 | 3d soil moisture/Tskin/ght(1) excl. catdef unless PEATCLSM tile | sfmc/sfds, Tb, SCF
! | & 1d snow analysis (Toure et al. 2018 empirical gain) |
! 13 | 3d soil moisture/Tskin/ght(1) excl. catdef unless PEATCLSM tile | sfmc/sfds, Tb
update_type = 0
out_obslog = .true.
out_ObsFcstAna = .false.
out_smapL4SMaup = .false.
! ---------------------------------------------------------------------
!
! Compact support parameters - for 3d updates
!
! All correlations vanish outside of an ellipse with semi-axes xcompact
! and ycompact
xcompact = 0. ! [deg] longitude
ycompact = 0. ! [deg] latitude
! ---------------------------------------------------------------------
!
! forecast error covariance inflaction factor
!
! - assigns more weight to observations in analysis by inflating forecast error covariance
! - works on std-dev, i.e., var_inflated = var * inflation_fac**2
! - typical values: 1 <= inflation_fac <= 1.5
! - to turn off, set to any negative real number
fcsterr_inflation_fac = -9999.
! ---------------------------------------------------------------------
!
! Definition of measurement species and parameters
!
! NOTE: When additional types of measurements are included here,
! at least the following parameters and subroutines must be adapted:
!
! - N_obs_species_nml in clsm_ensupd_glob_param.f90
! [- read_ens_upd_inputs()]
! [- collect_obs()]
! - read_obs()
! - get_obs_pred()
! - cat_enkf_update()
!
!
! Definition of obs_param_nml fields (see also enkf_types.F90):
!
! %descr = description
! %species = identifier for type of measurement
! %orbit = type of (half-)orbit
! 0 = n/a [eg., in situ obs]
! 1 = ascending
! 2 = descending
! 3 = ascending or descending
! 4 = geostationary
! %pol = polarization
! 0 = n/a [eg., multi-pol. retrieval]
! 1 = horizontal
! 2 = vertical
! 3 = ...
! %N_ang = # satellite viewing angles in species (radiance obs only)
! %ang = vector of satellite viewing angles
! %freq = frequency [Hz]
! %FOV = field-of-view *radius*, see NOTES below
! (if FOV==0. equate obs footprint w/ tile)
! %FOV_units = field-of-view units ('km' or 'deg'), see NOTES below
! %assim = Should this obs type be assimilated (state update)? (logical)
! %scale = Should this obs be scaled? (logical)
! %getinnov = Should innov be computed for this obs type (logical)
! (innovations are always computed if assim==.true.)
! %RTM_ID = ID of radiative transfer model to use for Tb forward modeling
! (subroutine get_obs_pred())
! 0 = none
! 1 = L-band tau-omega model as in De Lannoy et al. 2013 (doi:10.1175/JHM-D-12-092.1) (SMOS)
! 2 = same as 1 but without Pellarin atm corr (SMAP)
! 3 = same as 1 but with Mironov and SMAP L2_SM pol mixing (SMOS)
! 4 = same as 3 but without Pellarin atm corr (targeted for SMAP L4_SM Version 8)
! %bias_Npar = number of obs bias states tracked per day (integer)
! %bias_trel = e-folding time scale of obs bias memory [s]
! %bias_tcut = cutoff time for confident obs bias estimate [s]
! %nodata = no-data-value
! %varname = equivalent model variable name (for "Obs_pred")
! %units = units (eg., 'K' or 'm3/m3')
! %path = path to measurement files
! %name = name identifier for file containing measurements
! %maskpath = path to obs mask file
! %maskname = filename for obs mask
! %scalepath = path to file(s) with scaling parameters
! %scalename = filename for scaling parameters
! %flistpath = path to file with list of obs file names
! %flistname = name of file with list of obs file names
! %errstd = default obs error std
! %std_normal_max = maximum allowed perturbation (relative to N(0,1))
! %zeromean = enforce zero mean across ensemble
! %coarsen_pert = generate obs perturbations on coarser grid (see pert_param_type%coarsen)
! %xcorr = correlation length (deg) in longitude direction
! %ycorr = correlation length (deg) in latitude direction
!
! For observation perturbations, always use:
!
! tcorr = 0. (never temporally correlated)
! typ = 0 (always additive)
! ccorr = 0. (never cross-correlated)
!
! (these are specified in get_obs_pert_inputs() and not here)
!
!
! NOTES:
!
! Field-of-view (FOV) can be specified in units of [km] or [deg] lat/lon.
! Note the special case of FOV=0. below.
! If FOV is specified in units of [km], the FOV in units of [deg] lat/lon that
! is used to compute observation predictions will depend on latitude.
! If FOV is specified in units of [deg] lat/lon, its value remains constant and
! is independent of latitude.
! The choice of units also determines the shape function that is used to
! compute the observation predictions.
! Units of [km] are meant for observations that are based on relatively
! coarse-scale measurements (such as microwave data). The resolution of such obs
! in units of [km] is approximately constant across the globe and independent
! of latitude. Observation predictions are computed by averaging tile-based
! model forecasts out to a distance of fac_search_FOV_km*FOV using a Gaussian kernel,
! where fac_search_FOV_km=2.0 as of 28 March 2015.
! Specifically, the normalized square distance is defined as
!
! ndist2 = dx^2/FOV_x^2 + dy^2/FOV_y^2
!
! where FOV_x and dx are the meridional FOV and the meridional distance between the obs
! and the tile (in units of deg lat/lon), with FOV_x proportional to 1/cos(lat).
! FOV_y and dy are the corresponding zonal values.
! The weights are then proportional to
!
! exp( -0.5*ndist2 )
!
! The averaging is therefore over an ellipse in lat/lon space, with weights
! decreasing away from the center of the observation.
! A 2.0*FOV averaging footprint encapsulates about 91% of the power. A 1.0*FOV
! averaging footprint would encapsulate about 47% of the power. These numbers
! are meant to be approximately consistent with FOV numbers for microwave radiometers
! (see 3 Dec 2014 email from Ed Kim reproduced below).
! Note that weights are further adjusted based on tile area.
! Units of [deg] lat/lon are meant for observations that are based on
! relatively high-resolution measurements (such as infrared data). Such
! observations are often available on a lat/lon grid that is much coarser than
! the footprint of the underlying observations. The assimilated data product
! therefore has a resolution that varies with latitude. Observation predictions are
! computed by averaging over a constant kernel out to a distance of FOV.
! The averaging is therefore over a circle in lat/lon space, with weights that do not
! depend on the distance from the center of the observation.
! (Note that weights are further adjusted based on tile area.)
! If FOV=0., observation predictions are computed by assigning the model forecast
! associated with the tile to which the observation is formally assigned.
! This is useful if the resolution of the assimilated observations is higher
! than that of the model tile space. This might be the case for snow-cover-fraction
! observations. FOV=0 can also be useful for tile-based synthetic observations.
!
!
! ------------------------------------------------------------------------
!
! Date: Wed, 3 Dec 2014 11:21:30 -0600
! From: <edward.j.kim@nasa.gov>
! To: <rolf.h.reichle@nasa.gov>, <gabrielle.j.delannoy@nasa.gov>
! Subject: FW: [SMAP] antenna pattern question
!
! Hi Rolf & Gabrielle,
!
! First, a little terminology: the weighted integral is what Level 1 folks call
! "beam efficiency". So, apparently, Steven is assuming the "-3dB beam efficiency"
! is ~50%. The calculated [SMAP] beam efficiency within the -3dB contour is
! 53.40% (v-pol), 53.83% (h-pol).
! If you draw the -3dB contour on the Earth's surface, for h-pol, 53.83% of the energy
! comes from inside the contour, and 100-53.83 = 46.17% comes from outside the contour.
! The accuracy of the 1/10 and 1/100 digits is questionable, anyway.
! So, if you used 53% for v-pol and 54% for h-pol, you should be fine.
! I guess this means Steven was not far off, if he is using "50%."
! This -3dB beam efficiency means we have significant energy coming from outside
! the 3dB footprint, which is the footprint we use to come up with the "40 km" footprint
! size number.
! And, this is why many folks who use microwave instruments prefer to use a contour that
! encloses a higher % of the beam energy as a better measure of the footprint size.
! One such measure is the "main beam efficiency (MBE)." This beamwidth is usually taken
! to be 2.5 times the 3dB beamwidth. The corresponding footprint size is then
! 2.5x 40km = 100km.
! The last calculation put the MBE at 89.23 for V-pol and 89.33 for H-pol.
! So, for h-pol, 89.33% of the energy comes from inside a 100km footprint,
! and 100-89.33 = 10.67% from outside.
! - Ed
!
! ------------------------------------------------------------------------
!
! IMPORTANT: The number of measurement species defined below must *match*
! global parameter "N_obs_species_nml"
!
! Multi-angular observations (eg., SMOS) are defined as a single
! species here (in the nml file) and are later split into
! multiple species, each having a unique incidence angle
! (see subroutine read_ens_upd_inputs())
!
!
! ------------------------------------------------------------------------
! 1 = AMSR_E_L2_Soil_Moisture_A (A = ascending = "day")
obs_param_nml( 1)%descr = 'ae_l2_sm_a'
obs_param_nml( 1)%orbit = 1
obs_param_nml( 1)%pol = 0
obs_param_nml( 1)%N_ang = 0
obs_param_nml( 1)%freq = 10.65e9
obs_param_nml( 1)%FOV = 20.
obs_param_nml( 1)%FOV_units = 'km'
obs_param_nml( 1)%assim = .false.
obs_param_nml( 1)%scale = .false.
obs_param_nml( 1)%getinnov = .false.
obs_param_nml( 1)%RTM_ID = 0
obs_param_nml( 1)%bias_Npar = 0
obs_param_nml( 1)%bias_trel = 864000
obs_param_nml( 1)%bias_tcut = 432000
obs_param_nml( 1)%nodata = -9999.
obs_param_nml( 1)%varname = 'sfmc'
obs_param_nml( 1)%units = 'm3/m3'
obs_param_nml( 1)%path = '/land/l_data/AMSR/data/AMSR_E_L2_Land_V001/'
obs_param_nml( 1)%name = 'AMSR_E_L2_Land_'
obs_param_nml( 1)%maskpath = ''
obs_param_nml( 1)%maskname = ''
obs_param_nml( 1)%scalepath = ''
obs_param_nml( 1)%scalename = ''
obs_param_nml( 1)%flistpath = ''
obs_param_nml( 1)%flistname = ''
obs_param_nml( 1)%errstd = .02
obs_param_nml( 1)%std_normal_max = 2.5
obs_param_nml( 1)%zeromean = .true.
obs_param_nml( 1)%coarsen_pert = .false.
obs_param_nml( 1)%xcorr = 0.25
obs_param_nml( 1)%ycorr = 0.25
obs_param_nml( 1)%adapt = 0
! -------------------
!
! 2 = AMSR_E_L2_Soil_Moisture_D (D = descending = "night")
obs_param_nml( 2)%descr = 'ae_l2_sm_d'
obs_param_nml( 2)%orbit = 2
obs_param_nml( 2)%pol = 0
obs_param_nml( 2)%N_ang = 0
obs_param_nml( 2)%freq = 10.65e9
obs_param_nml( 2)%FOV = 20.
obs_param_nml( 2)%FOV_units = 'km'
obs_param_nml( 2)%assim = .false.
obs_param_nml( 2)%scale = .false.
obs_param_nml( 2)%getinnov = .false.
obs_param_nml( 2)%RTM_ID = 0
obs_param_nml( 2)%bias_Npar = 0
obs_param_nml( 2)%bias_trel = 864000
obs_param_nml( 2)%bias_tcut = 432000
obs_param_nml( 2)%nodata = -9999.
obs_param_nml( 2)%varname = 'sfmc'
obs_param_nml( 2)%units = 'm3/m3'
obs_param_nml( 2)%path = '/land/l_data/AMSR/data/AMSR_E_L2_Land_V001/'
obs_param_nml( 2)%name = 'AMSR_E_L2_Land_'
obs_param_nml( 2)%maskpath = ''
obs_param_nml( 2)%maskname = ''
obs_param_nml( 2)%scalepath = ''
obs_param_nml( 2)%scalename = ''
obs_param_nml( 2)%flistpath = ''
obs_param_nml( 2)%flistname = ''
obs_param_nml( 2)%errstd = .02
obs_param_nml( 2)%std_normal_max = 2.5
obs_param_nml( 2)%zeromean = .true.
obs_param_nml( 2)%coarsen_pert = .false.
obs_param_nml( 2)%xcorr = 0.25
obs_param_nml( 2)%ycorr = 0.25
obs_param_nml( 2)%adapt = 0
! --------------------------------------------------------------------
!
! 3 = ISCCP_Tskin_GSWP2_grid_V1
obs_param_nml( 3)%descr = 'isccp_tskin_gswp2_v1'
obs_param_nml( 3)%orbit = 4
obs_param_nml( 3)%pol = 0
obs_param_nml( 3)%N_ang = 0
obs_param_nml( 3)%freq = 0.
obs_param_nml( 3)%FOV = 0.6
obs_param_nml( 3)%FOV_units = 'deg'
obs_param_nml( 3)%assim = .false.
obs_param_nml( 3)%scale = .false.
obs_param_nml( 3)%getinnov = .false.
obs_param_nml( 3)%RTM_ID = 0
obs_param_nml( 3)%bias_Npar = 0
obs_param_nml( 3)%bias_trel = 864000
obs_param_nml( 3)%bias_tcut = 432000
obs_param_nml( 3)%nodata = -9999.
obs_param_nml( 3)%varname = 'tsurf'
obs_param_nml( 3)%units = 'K'
obs_param_nml( 3)%path = '/land/l_data/ISCCP/GSWP2_1by1_V1/'
obs_param_nml( 3)%name = 'isccpdx_tskin.'
obs_param_nml( 3)%maskpath = ''
obs_param_nml( 3)%maskname = ''
obs_param_nml( 3)%scalepath = ''
obs_param_nml( 3)%scalename = ''
obs_param_nml( 3)%flistpath = ''
obs_param_nml( 3)%flistname = ''
obs_param_nml( 3)%errstd = 3.
obs_param_nml( 3)%std_normal_max = 2.5
obs_param_nml( 3)%zeromean = .true.
obs_param_nml( 3)%coarsen_pert = .false.
obs_param_nml( 3)%xcorr = 0.6
obs_param_nml( 3)%ycorr = 0.6
obs_param_nml( 3)%adapt = 0
! --------------------------------------------------------------------
!
! 4 = RedArkOSSE_sm
obs_param_nml( 4)%descr = 'RedArkOSSE_sm'
obs_param_nml( 4)%orbit = 0
obs_param_nml( 4)%pol = 0
obs_param_nml( 4)%N_ang = 0
obs_param_nml( 4)%freq = 0.
obs_param_nml( 4)%FOV = 0.
obs_param_nml( 4)%FOV_units = 'deg'
obs_param_nml( 4)%assim = .false.
obs_param_nml( 4)%scale = .false.
obs_param_nml( 4)%getinnov = .false.
obs_param_nml( 4)%RTM_ID = 0
obs_param_nml( 4)%bias_Npar = 0
obs_param_nml( 4)%bias_trel = 864000
obs_param_nml( 4)%bias_tcut = 432000
obs_param_nml( 4)%nodata = -999.
obs_param_nml( 4)%varname = 'sfmc'
obs_param_nml( 4)%units = 'm3/m3'
obs_param_nml( 4)%path = '/land/l_data/RedArk/Retrievals_36km/retrievals_20060508/'
obs_param_nml( 4)%name = 'SM_retrieval.'
obs_param_nml( 4)%maskpath = ''
obs_param_nml( 4)%maskname = ''
obs_param_nml( 4)%scalepath = '.'
obs_param_nml( 4)%scalename = '.'
obs_param_nml( 4)%flistpath = ''
obs_param_nml( 4)%flistname = ''
obs_param_nml( 4)%errstd = .04
obs_param_nml( 4)%std_normal_max = 2.5
obs_param_nml( 4)%zeromean = .true.
obs_param_nml( 4)%coarsen_pert = .false.
obs_param_nml( 4)%xcorr = 0.
obs_param_nml( 4)%ycorr = 0.
obs_param_nml( 4)%adapt = 0
! -------------------
!
! 5 = RedArkOSSE_truth_50mm
obs_param_nml( 5)%descr = 'RedArkOSSE_truth_50mm'
obs_param_nml( 5)%orbit = 0
obs_param_nml( 5)%pol = 0
obs_param_nml( 5)%N_ang = 0
obs_param_nml( 5)%freq = 0.
obs_param_nml( 5)%FOV = 0.
obs_param_nml( 5)%FOV_units = 'deg'
obs_param_nml( 5)%assim = .false.
obs_param_nml( 5)%scale = .false.
obs_param_nml( 5)%getinnov = .false.
obs_param_nml( 5)%RTM_ID = 0
obs_param_nml( 5)%bias_Npar = 0
obs_param_nml( 5)%bias_trel = 864000
obs_param_nml( 5)%bias_tcut = 432000
obs_param_nml( 5)%nodata = -999.
obs_param_nml( 5)%varname = 'sfmc'
obs_param_nml( 5)%units = 'm3/m3'
obs_param_nml( 5)%path = '/land/l_data/RedArk/Truth/50mm_Soil_Moisture_Truth/'
obs_param_nml( 5)%name = 'red_ark_50mm.sm.'
obs_param_nml( 5)%maskpath = ''
obs_param_nml( 5)%maskname = ''
obs_param_nml( 5)%scalepath = '.'
obs_param_nml( 5)%scalename = '.'
obs_param_nml( 5)%flistpath = ''
obs_param_nml( 5)%flistname = ''
obs_param_nml( 5)%errstd = .0
obs_param_nml( 5)%std_normal_max = 2.5
obs_param_nml( 5)%zeromean = .true.
obs_param_nml( 5)%coarsen_pert = .false.
obs_param_nml( 5)%xcorr = 0.
obs_param_nml( 5)%ycorr = 0.
obs_param_nml( 5)%adapt = 0
! -------------------
!
! 6 = RedArkOSSE_truth_400mm
obs_param_nml( 6)%descr = 'RedArkOSSE_truth_400mm'
obs_param_nml( 6)%orbit = 0
obs_param_nml( 6)%pol = 0
obs_param_nml( 6)%N_ang = 0
obs_param_nml( 6)%freq = 0.
obs_param_nml( 6)%FOV = 0.
obs_param_nml( 6)%FOV_units = 'deg'
obs_param_nml( 6)%assim = .false.
obs_param_nml( 6)%scale = .false.
obs_param_nml( 6)%getinnov = .false.
obs_param_nml( 6)%RTM_ID = 0
obs_param_nml( 6)%bias_Npar = 0
obs_param_nml( 6)%bias_trel = 864000
obs_param_nml( 6)%bias_tcut = 432000
obs_param_nml( 6)%nodata = -999.
obs_param_nml( 6)%varname = 'rzmc'
obs_param_nml( 6)%units = 'm3/m3'
obs_param_nml( 6)%path = '/land/l_data/RedArk/Truth/400mm_Soil_Moisture_Truth/'
obs_param_nml( 6)%name = 'red_ark_400mm.sm.'
obs_param_nml( 6)%maskpath = ''
obs_param_nml( 6)%maskname = ''
obs_param_nml( 6)%scalepath = '.'
obs_param_nml( 6)%scalename = '.'
obs_param_nml( 6)%flistpath = ''
obs_param_nml( 6)%flistname = ''
obs_param_nml( 6)%errstd = .0
obs_param_nml( 6)%std_normal_max = 2.5
obs_param_nml( 6)%zeromean = .true.
obs_param_nml( 6)%coarsen_pert = .false.
obs_param_nml( 6)%xcorr = 0.
obs_param_nml( 6)%ycorr = 0.
obs_param_nml( 6)%adapt = 0
! --------------------------------------------------------------------
!
! 7 = RedArkOSSE_CLSMsynthSM
obs_param_nml( 7)%descr = 'RedArkOSSE_CLSMsynthSM'
obs_param_nml( 7)%orbit = 0
obs_param_nml( 7)%pol = 0
obs_param_nml( 7)%N_ang = 0
obs_param_nml( 7)%freq = 0.
obs_param_nml( 7)%FOV = 0.
obs_param_nml( 7)%FOV_units = 'deg'
obs_param_nml( 7)%assim = .false.
obs_param_nml( 7)%scale = .false.
obs_param_nml( 7)%getinnov = .false.
obs_param_nml( 7)%RTM_ID = 0
obs_param_nml( 7)%bias_Npar = 0
obs_param_nml( 7)%bias_trel = 864000
obs_param_nml( 7)%bias_tcut = 432000
obs_param_nml( 7)%nodata = -9999.
obs_param_nml( 7)%varname = 'sfmc'
obs_param_nml( 7)%units = 'm3/m3'
obs_param_nml( 7)%path = '/land/l_data/RedArk_OSSE/data/Retrievals_CLSM_synth/M0001_P0001_R0001_URI/std_synth_obs_0.020/'
obs_param_nml( 7)%name = 'CLSM_synth_sm.'
obs_param_nml( 7)%maskpath = ''
obs_param_nml( 7)%maskname = ''
obs_param_nml( 7)%scalepath = '.'
obs_param_nml( 7)%scalename = '.'
obs_param_nml( 7)%flistpath = ''
obs_param_nml( 7)%flistname = ''
obs_param_nml( 7)%errstd = .04
obs_param_nml( 7)%std_normal_max = 2.5
obs_param_nml( 7)%zeromean = .true.
obs_param_nml( 7)%coarsen_pert = .false.
obs_param_nml( 7)%xcorr = 0.
obs_param_nml( 7)%ycorr = 0.
obs_param_nml( 7)%adapt = 0
! --------------------------------------------------------------------
!
! 8 = VivianaOK_CLSMsynthSM
obs_param_nml( 8)%descr = 'VivianaOK_CLSMsynthSM'
obs_param_nml( 8)%orbit = 0
obs_param_nml( 8)%pol = 0
obs_param_nml( 8)%N_ang = 0
obs_param_nml( 8)%freq = 0.
obs_param_nml( 8)%FOV = 0.
obs_param_nml( 8)%FOV_units = 'deg'
obs_param_nml( 8)%assim = .false.
obs_param_nml( 8)%scale = .false.
obs_param_nml( 8)%getinnov = .false.
obs_param_nml( 8)%RTM_ID = 0
obs_param_nml( 8)%bias_Npar = 0
obs_param_nml( 8)%bias_trel = 864000
obs_param_nml( 8)%bias_tcut = 432000
obs_param_nml( 8)%nodata = -9999.
obs_param_nml( 8)%varname = 'sfmc'
obs_param_nml( 8)%units = 'm3/m3'
obs_param_nml( 8)%path = '/discover/nobackup/vmaggion/Synth_sfmc/radar_sim/std_synth_sfmc_0.040/'
obs_param_nml( 8)%name = 'synth_sfmc_VivianaOK_'
obs_param_nml( 8)%maskpath = ''
obs_param_nml( 8)%maskname = ''
obs_param_nml( 8)%scalepath = '.'
obs_param_nml( 8)%scalename = '.'
obs_param_nml( 8)%flistpath = ''
obs_param_nml( 8)%flistname = ''
obs_param_nml( 8)%errstd = .04
obs_param_nml( 8)%std_normal_max = 2.5
obs_param_nml( 8)%zeromean = .true.
obs_param_nml( 8)%coarsen_pert = .false.
obs_param_nml( 8)%xcorr = 0.
obs_param_nml( 8)%ycorr = 0.
obs_param_nml( 8)%adapt = 0
! --------------------------------------------------------------------
!
! 9 = AMSR_E_sm_LPRM_A_C (A = ascending = "day", C-band)
obs_param_nml( 9)%descr = 'ae_sm_LPRM_a_C'
obs_param_nml( 9)%orbit = 1
obs_param_nml( 9)%pol = 0
obs_param_nml( 9)%N_ang = 0
obs_param_nml( 9)%freq = 6.925e9
obs_param_nml( 9)%FOV = 20.
obs_param_nml( 9)%FOV_units = 'km'
obs_param_nml( 9)%assim = .false.
obs_param_nml( 9)%scale = .false.
obs_param_nml( 9)%getinnov = .false.
obs_param_nml( 9)%RTM_ID = 0
obs_param_nml( 9)%bias_Npar = 0
obs_param_nml( 9)%bias_trel = 864000
obs_param_nml( 9)%bias_tcut = 432000
obs_param_nml( 9)%nodata = -9999.
obs_param_nml( 9)%varname = 'sfmc'
obs_param_nml( 9)%units = 'm3/m3'
obs_param_nml( 9)%path = '/land/l_data/AMSR/data/AMSR_E_sm_LPRM/L2_EASE/bin/'
obs_param_nml( 9)%name = 'AMSRsmUVA.EASE.v03.'
obs_param_nml( 9)%maskpath = ''
obs_param_nml( 9)%maskname = ''
obs_param_nml( 9)%scalepath = ''
obs_param_nml( 9)%scalename = ''
obs_param_nml( 9)%flistpath = ''
obs_param_nml( 9)%flistname = ''
obs_param_nml( 9)%errstd = .04
obs_param_nml( 9)%std_normal_max = 2.5
obs_param_nml( 9)%zeromean = .true.
obs_param_nml( 9)%coarsen_pert = .false.
obs_param_nml( 9)%xcorr = 0.25
obs_param_nml( 9)%ycorr = 0.25
obs_param_nml( 9)%adapt = 0
! -------------------
!
! 10 = AMSR_E_sm_LPRM_D_C (D = descending = "night", C-band)
obs_param_nml(10)%descr = 'ae_sm_LPRM_d_C'
obs_param_nml(10)%orbit = 2
obs_param_nml(10)%pol = 0
obs_param_nml(10)%N_ang = 0
obs_param_nml(10)%freq = 6.925e9
obs_param_nml(10)%FOV = 20.
obs_param_nml(10)%FOV_units = 'km'
obs_param_nml(10)%assim = .false.
obs_param_nml(10)%scale = .false.
obs_param_nml(10)%getinnov = .false.
obs_param_nml(10)%RTM_ID = 0
obs_param_nml(10)%bias_Npar = 0
obs_param_nml(10)%bias_trel = 864000
obs_param_nml(10)%bias_tcut = 432000
obs_param_nml(10)%nodata = -9999.
obs_param_nml(10)%varname = 'sfmc'
obs_param_nml(10)%units = 'm3/m3'
obs_param_nml(10)%path = '/land/l_data/AMSR/data/AMSR_E_sm_LPRM/L2_EASE/bin/'
obs_param_nml(10)%name = 'AMSRsmUVA.EASE.v03.'
obs_param_nml(10)%maskpath = ''
obs_param_nml(10)%maskname = ''
obs_param_nml(10)%scalepath = ''
obs_param_nml(10)%scalename = ''
obs_param_nml(10)%flistpath = ''
obs_param_nml(10)%flistname = ''
obs_param_nml(10)%errstd = .04
obs_param_nml(10)%std_normal_max = 2.5
obs_param_nml(10)%zeromean = .true.
obs_param_nml(10)%coarsen_pert = .false.
obs_param_nml(10)%xcorr = 0.25
obs_param_nml(10)%ycorr = 0.25
obs_param_nml(10)%adapt = 0
! -------------------
!
! 11 = AMSR_E_sm_LPRM_A_X (A = ascending = "day", X-band)
obs_param_nml(11)%descr = 'ae_sm_LPRM_a_X'
obs_param_nml(11)%orbit = 1
obs_param_nml(11)%pol = 0
obs_param_nml(11)%N_ang = 0
obs_param_nml(11)%freq = 10.65e9
obs_param_nml(11)%FOV = 20.
obs_param_nml(11)%FOV_units = 'km'
obs_param_nml(11)%assim = .false.
obs_param_nml(11)%scale = .false.
obs_param_nml(11)%getinnov = .false.
obs_param_nml(11)%RTM_ID = 0
obs_param_nml(11)%bias_Npar = 0
obs_param_nml(11)%bias_trel = 864000
obs_param_nml(11)%bias_tcut = 432000
obs_param_nml(11)%nodata = -9999.
obs_param_nml(11)%varname = 'sfmc'
obs_param_nml(11)%units = 'm3/m3'
obs_param_nml(11)%path = '/land/l_data/AMSR/data/AMSR_E_sm_LPRM/L2_EASE/bin/'
obs_param_nml(11)%name = 'AMSRsmUVA.EASE.v03.'
obs_param_nml(11)%maskpath = ''
obs_param_nml(11)%maskname = ''
obs_param_nml(11)%scalepath = ''
obs_param_nml(11)%scalename = ''
obs_param_nml(11)%flistpath = ''
obs_param_nml(11)%flistname = ''
obs_param_nml(11)%errstd = .04
obs_param_nml(11)%std_normal_max = 2.5
obs_param_nml(11)%zeromean = .true.
obs_param_nml(11)%coarsen_pert = .false.
obs_param_nml(11)%xcorr = 0.25
obs_param_nml(11)%ycorr = 0.25
obs_param_nml(11)%adapt = 0
! -------------------
!
! 12 = AMSR_E_sm_LPRM_D_X (D = descending = "night", X-band)
obs_param_nml(12)%descr = 'ae_sm_LPRM_d_X'
obs_param_nml(12)%orbit = 2
obs_param_nml(12)%pol = 0
obs_param_nml(12)%N_ang = 0
obs_param_nml(12)%freq = 10.65e9
obs_param_nml(12)%FOV = 20.
obs_param_nml(12)%FOV_units = 'km'
obs_param_nml(12)%assim = .false.
obs_param_nml(12)%scale = .false.
obs_param_nml(12)%getinnov = .false.
obs_param_nml(12)%RTM_ID = 0
obs_param_nml(12)%bias_Npar = 0
obs_param_nml(12)%bias_trel = 864000
obs_param_nml(12)%bias_tcut = 432000
obs_param_nml(12)%nodata = -9999.
obs_param_nml(12)%varname = 'sfmc'
obs_param_nml(12)%units = 'm3/m3'
obs_param_nml(12)%path = '/land/l_data/AMSR/data/AMSR_E_sm_LPRM/L2_EASE/bin/'
obs_param_nml(12)%name = 'AMSRsmUVA.EASE.v03.'
obs_param_nml(12)%maskpath = ''
obs_param_nml(12)%maskname = ''
obs_param_nml(12)%scalepath = ''
obs_param_nml(12)%scalename = ''
obs_param_nml(12)%flistpath = ''
obs_param_nml(12)%flistname = ''
obs_param_nml(12)%errstd = .04
obs_param_nml(12)%std_normal_max = 2.5
obs_param_nml(12)%zeromean = .true.
obs_param_nml(12)%coarsen_pert = .false.
obs_param_nml(12)%xcorr = 0.25
obs_param_nml(12)%ycorr = 0.25
obs_param_nml(12)%adapt = 0
! --------------------------------------------------------------------
!
! 13 = ASCAT_SM_A (ASCAT soil moisture ascending)
!
! ASCAT: VV-pol, incidence angle 25-65 deg
! for now keep N_ang=0, pol=0
! - reichle, 30 Jun 2015
obs_param_nml(13)%descr = 'ASCAT_SM_A'
obs_param_nml(13)%orbit = 1
obs_param_nml(13)%pol = 0
obs_param_nml(13)%N_ang = 0
obs_param_nml(13)%freq = 5.255e9
obs_param_nml(13)%FOV = 20.
obs_param_nml(13)%FOV_units = 'km'
obs_param_nml(13)%assim = .false.
obs_param_nml(13)%scale = .false.
obs_param_nml(13)%getinnov = .false.
obs_param_nml(13)%RTM_ID = 0
obs_param_nml(13)%bias_Npar = 0
obs_param_nml(13)%bias_trel = 864000
obs_param_nml(13)%bias_tcut = 432000
obs_param_nml(13)%nodata = -9999.
obs_param_nml(13)%varname = 'sfmc'
obs_param_nml(13)%units = 'm3/m3'
obs_param_nml(13)%path = '/discover/nobackup/rreichle/l_data/ASCAT/TUW_W5.4/EASE/CONUS/bin/'
obs_param_nml(13)%name = 'SDS_'
obs_param_nml(13)%maskpath = ''
obs_param_nml(13)%maskname = ''
obs_param_nml(13)%scalepath = ''
obs_param_nml(13)%scalename = ''
obs_param_nml(13)%flistpath = ''
obs_param_nml(13)%flistname = ''
obs_param_nml(13)%errstd = .04
obs_param_nml(13)%std_normal_max = 2.5
obs_param_nml(13)%zeromean = .true.
obs_param_nml(13)%coarsen_pert = .false.
obs_param_nml(13)%xcorr = 0.25
obs_param_nml(13)%ycorr = 0.25
obs_param_nml(13)%adapt = 0
! -------------------
!
! 14 = ASCAT_SM_D (ASCAT soil moisture descending)
!
! TO DO: What is pol of backscatter used in retrieval?
! TO DO: How deal w/ inc angle?
! http://oiswww.eumetsat.org/WEBOPS/eps-pg/ASCAT/ASCAT-PG-4ProdOverview.htm
obs_param_nml(14)%descr = 'ASCAT_SM_D'
obs_param_nml(14)%orbit = 2
obs_param_nml(14)%pol = 0
obs_param_nml(14)%N_ang = 0
obs_param_nml(14)%freq = 5.255e9
obs_param_nml(14)%FOV = 20.
obs_param_nml(14)%FOV_units = 'km'
obs_param_nml(14)%assim = .false.
obs_param_nml(14)%scale = .false.
obs_param_nml(14)%getinnov = .false.
obs_param_nml(14)%RTM_ID = 0
obs_param_nml(14)%bias_Npar = 0
obs_param_nml(14)%bias_trel = 864000
obs_param_nml(14)%bias_tcut = 432000
obs_param_nml(14)%nodata = -9999.
obs_param_nml(14)%varname = 'sfmc'
obs_param_nml(14)%units = 'm3/m3'
obs_param_nml(14)%path = '/discover/nobackup/rreichle/l_data/ASCAT/TUW_W5.4/EASE/CONUS/bin/'
obs_param_nml(14)%name = 'SDS_'
obs_param_nml(14)%maskpath = ''
obs_param_nml(14)%maskname = ''
obs_param_nml(14)%scalepath = ''
obs_param_nml(14)%scalename = ''
obs_param_nml(14)%flistpath = ''
obs_param_nml(14)%flistname = ''
obs_param_nml(14)%errstd = .04
obs_param_nml(14)%std_normal_max = 2.5
obs_param_nml(14)%zeromean = .true.
obs_param_nml(14)%coarsen_pert = .false.
obs_param_nml(14)%xcorr = 0.25
obs_param_nml(14)%ycorr = 0.25
obs_param_nml(14)%adapt = 0
! --------------------------------------------------------------------
!
! 15 = SMOS_SM_A (SMOS soil moisture ascending)
obs_param_nml(15)%descr = 'SMOS_SM_A'
obs_param_nml(15)%orbit = 1
obs_param_nml(15)%pol = 0
obs_param_nml(15)%N_ang = 0
obs_param_nml(15)%freq = 1.41e9
obs_param_nml(15)%FOV = 20.
obs_param_nml(15)%FOV_units = 'km'
obs_param_nml(15)%assim = .false.
obs_param_nml(15)%scale = .false.
obs_param_nml(15)%getinnov = .false.
obs_param_nml(15)%RTM_ID = 0
obs_param_nml(15)%bias_Npar = 0
obs_param_nml(15)%bias_trel = 864000
obs_param_nml(15)%bias_tcut = 432000
obs_param_nml(15)%nodata = -9999.
obs_param_nml(15)%varname = 'sfmc'
obs_param_nml(15)%units = 'm3/m3'
obs_param_nml(15)%path = '/discover/nobackup/projects/gmao/ssd/land/l_data/SMOS/EASEv2/ESA_REPR/SMOS_M36_SMUDP2/'
obs_param_nml(15)%name = ''
obs_param_nml(15)%maskpath = ''
obs_param_nml(15)%maskname = ''
obs_param_nml(15)%scalepath = ''
obs_param_nml(15)%scalename = ''
obs_param_nml(15)%flistpath = ''
obs_param_nml(15)%flistname = ''
obs_param_nml(15)%errstd = .04
obs_param_nml(15)%std_normal_max = 2.5
obs_param_nml(15)%zeromean = .true.
obs_param_nml(15)%coarsen_pert = .false.
obs_param_nml(15)%xcorr = 0.25
obs_param_nml(15)%ycorr = 0.25
obs_param_nml(15)%adapt = 0
! -------------------
!
! 16 = SMOS_SM_D (SMOS soil moisture descending)
obs_param_nml(16)%descr = 'SMOS_SM_D'
obs_param_nml(16)%orbit = 2
obs_param_nml(16)%pol = 0
obs_param_nml(16)%N_ang = 0
obs_param_nml(16)%freq = 1.41e9
obs_param_nml(16)%FOV = 20.
obs_param_nml(16)%FOV_units = 'km'
obs_param_nml(16)%assim = .false.
obs_param_nml(16)%scale = .false.
obs_param_nml(16)%getinnov = .false.
obs_param_nml(16)%RTM_ID = 0
obs_param_nml(16)%bias_Npar = 0
obs_param_nml(16)%bias_trel = 864000
obs_param_nml(16)%bias_tcut = 432000
obs_param_nml(16)%nodata = -9999.
obs_param_nml(16)%varname = 'sfmc'
obs_param_nml(16)%units = 'm3/m3'
obs_param_nml(16)%path = '/discover/nobackup/projects/gmao/ssd/land/l_data/SMOS/EASEv2/ESA_REPR/SMOS_M36_SMUDP2/'
obs_param_nml(16)%name = ''
obs_param_nml(16)%maskpath = ''
obs_param_nml(16)%maskname = ''
obs_param_nml(16)%scalepath = ''
obs_param_nml(16)%scalename = ''
obs_param_nml(16)%flistpath = ''
obs_param_nml(16)%flistname = ''
obs_param_nml(16)%errstd = .04
obs_param_nml(16)%std_normal_max = 2.5
obs_param_nml(16)%zeromean = .true.
obs_param_nml(16)%coarsen_pert = .false.
obs_param_nml(16)%xcorr = 0.25
obs_param_nml(16)%ycorr = 0.25
obs_param_nml(16)%adapt = 0
! --------------------------------------------------------------------
!
! SMOS multi-angular brightness temperature
!
! "A" = ascending (6am *SMOS* overpass)
! "D" = descending (6pm *SMOS* overpass)
!
! "Tbh" = h-pol Tb
! "Tbv" = v-pol Tb
!
!
! "Regular" vs. "fitted" SMOS brightness temperatures:
!
! "Regular" Tb data ('SMOS_reg_Tb*'):
! Derived from SMOS SCLF1C data by Gabrielle De Lannoy. Observations within
! one-degree angular bins for a given time and location are averaged.
! Various quality controls steps are applied.
! A typical assimilation setup uses 7 angles.
! For details see De Lannoy et al (2013) doi:10.1175/JHM-D-12-092.1.
!
! "Fitted" Tb data ('SMOS_fit_Tb*'):
! Derived from "regular" SMOS Tb data by Gabrielle De Lannoy. Observations
! for a given time and location derived by fitting across available incidence
! angles. The resulting fitted observation at 40 deg incidence angle corresponds
! roughly to what the SMAP radiometer observes (a.k.a. "SMOS40").
! A typical assimilation setup uses only one angle.
!
!
! Frequency:
!
! Date: Wed, 8 Jun 2011 02:34:40 -0500
! From: <delphine.leroux@cesbio.cnes.fr>
! To: <gabrielle.j.delannoy@nasa.gov>
!
! In the ATBD it is written that the central frequency is 1.413 GHz. I
! have asked around but it seems more complicated than expected because
! the 64 antennas are working around 1.410 GHz (+-0.008 GHz) and there is
! no exact value for the frequency (mostly because the frequency of each
! antenna depends on the temperature...). Here we work with 1.413 GHz.
!
! -------------------
!
! 17 = SMOS_reg_Tbh_A
obs_param_nml(17)%descr = 'SMOS_reg_Tbh_A'
obs_param_nml(17)%orbit = 1
obs_param_nml(17)%pol = 1
obs_param_nml(17)%N_ang = 7
obs_param_nml(17)%ang(1) = 30.
obs_param_nml(17)%ang(2) = 35.
obs_param_nml(17)%ang(3) = 40.
obs_param_nml(17)%ang(4) = 45.
obs_param_nml(17)%ang(5) = 50.
obs_param_nml(17)%ang(6) = 55.
obs_param_nml(17)%ang(7) = 60.
obs_param_nml(17)%freq = 1.41e9
obs_param_nml(17)%FOV = 20.
obs_param_nml(17)%FOV_units = 'km'
obs_param_nml(17)%assim = .false.
obs_param_nml(17)%scale = .false.
obs_param_nml(17)%getinnov = .false.
obs_param_nml(17)%RTM_ID = 2
obs_param_nml(17)%bias_Npar = 0
obs_param_nml(17)%bias_trel = 864000
obs_param_nml(17)%bias_tcut = 432000
obs_param_nml(17)%nodata = -9999.
obs_param_nml(17)%varname = 'Tb'
obs_param_nml(17)%units = 'K'
obs_param_nml(17)%path = '/discover/nobackup/projects/gmao/ssd/land/l_data/SMOS/EASEv2/ESA_REPR/SMOS_M36_SCLF1C_reg_nosky_noatm_v620_ESA_v102/'
obs_param_nml(17)%name = ''
obs_param_nml(17)%maskpath = ''
obs_param_nml(17)%maskname = ''
obs_param_nml(17)%scalepath = ''
obs_param_nml(17)%scalename = ''
obs_param_nml(17)%flistpath = ''
obs_param_nml(17)%flistname = ''
obs_param_nml(17)%errstd = 4.
obs_param_nml(17)%std_normal_max = 2.5
obs_param_nml(17)%zeromean = .true.
obs_param_nml(17)%coarsen_pert = .false.
obs_param_nml(17)%xcorr = 0.25
obs_param_nml(17)%ycorr = 0.25
obs_param_nml(17)%adapt = 0
! -------------------
!
! 18 = SMOS_reg_Tbh_D
obs_param_nml(18)%descr = 'SMOS_reg_Tbh_D'
obs_param_nml(18)%orbit = 2
obs_param_nml(18)%pol = 1
obs_param_nml(18)%N_ang = 7
obs_param_nml(18)%ang(1) = 30.
obs_param_nml(18)%ang(2) = 35.
obs_param_nml(18)%ang(3) = 40.
obs_param_nml(18)%ang(4) = 45.
obs_param_nml(18)%ang(5) = 50.
obs_param_nml(18)%ang(6) = 55.
obs_param_nml(18)%ang(7) = 60.
obs_param_nml(18)%freq = 1.41e9
obs_param_nml(18)%FOV = 20.
obs_param_nml(18)%FOV_units = 'km'
obs_param_nml(18)%assim = .false.
obs_param_nml(18)%scale = .false.
obs_param_nml(18)%getinnov = .false.
obs_param_nml(18)%RTM_ID = 2
obs_param_nml(18)%bias_Npar = 0
obs_param_nml(18)%bias_trel = 864000
obs_param_nml(18)%bias_tcut = 432000
obs_param_nml(18)%nodata = -9999.
obs_param_nml(18)%varname = 'Tb'
obs_param_nml(18)%units = 'K'
obs_param_nml(18)%path = '/discover/nobackup/projects/gmao/ssd/land/l_data/SMOS/EASEv2/ESA_REPR/SMOS_M36_SCLF1C_reg_nosky_noatm_v620_ESA_v102/'
obs_param_nml(18)%name = ''
obs_param_nml(18)%maskpath = ''
obs_param_nml(18)%maskname = ''
obs_param_nml(18)%scalepath = ''
obs_param_nml(18)%scalename = ''
obs_param_nml(18)%flistpath = ''
obs_param_nml(18)%flistname = ''
obs_param_nml(18)%errstd = 4.
obs_param_nml(18)%std_normal_max = 2.5
obs_param_nml(18)%zeromean = .true.
obs_param_nml(18)%coarsen_pert = .false.
obs_param_nml(18)%xcorr = 0.25
obs_param_nml(18)%ycorr = 0.25
obs_param_nml(18)%adapt = 0
! -------------------
!
! 19 = SMOS_reg_Tbv_A
obs_param_nml(19)%descr = 'SMOS_reg_Tbv_A'
obs_param_nml(19)%orbit = 1
obs_param_nml(19)%pol = 2
obs_param_nml(19)%N_ang = 7
obs_param_nml(19)%ang(1) = 30.
obs_param_nml(19)%ang(2) = 35.
obs_param_nml(19)%ang(3) = 40.
obs_param_nml(19)%ang(4) = 45.
obs_param_nml(19)%ang(5) = 50.
obs_param_nml(19)%ang(6) = 55.
obs_param_nml(19)%ang(7) = 60.
obs_param_nml(19)%freq = 1.41e9
obs_param_nml(19)%FOV = 20.
obs_param_nml(19)%FOV_units = 'km'
obs_param_nml(19)%assim = .false.
obs_param_nml(19)%scale = .false.
obs_param_nml(19)%getinnov = .false.
obs_param_nml(19)%RTM_ID = 2
obs_param_nml(19)%bias_Npar = 0
obs_param_nml(19)%bias_trel = 864000
obs_param_nml(19)%bias_tcut = 432000
obs_param_nml(19)%nodata = -9999.
obs_param_nml(19)%varname = 'Tb'
obs_param_nml(19)%units = 'K'
obs_param_nml(19)%path = '/discover/nobackup/projects/gmao/ssd/land/l_data/SMOS/EASEv2/ESA_REPR/SMOS_M36_SCLF1C_reg_nosky_noatm_v620_ESA_v102/'
obs_param_nml(19)%name = ''
obs_param_nml(19)%maskpath = ''
obs_param_nml(19)%maskname = ''
obs_param_nml(19)%scalepath = ''