da_residual_polaramv.inc

1 subroutine da_residual_polaramv(oi, y, re,                        &
2                                         np_missing, np_bad_data,          &
3                                         np_obs_used, np_available)
4    !-------------------------------------------------------------------------
5    ! Purpose: TBD
6    !-------------------------------------------------------------------------
7 
8    implicit none
9 
10    type (ob_type), intent(in)        :: oi     ! Innovation vector (O-B).
11    type (y_type) , intent(in)        :: y      ! y = H (xa)
12    type (y_type) , intent(inout)     :: re     ! Residual vector (O-A).
13 
14    integer       , intent(inout)     :: np_available, np_obs_used,          &
15                                         np_missing  , np_bad_data
16 
17    type (bad_data_type)              :: n_obs_bad
18    integer                           :: n, k
19 
20    if (oi%num_polaramv > 0) then
21 
22       n_obs_bad % u % num = number_type(0, 0, 0)
23       n_obs_bad % v % num = number_type(0, 0, 0)
24 
25       do n=1, oi%num_polaramv
26          do k=1, oi%polaramv(n)%info%levels
27             np_available = np_available + 2
28 
29             re%polaramv(n)%u(k) = da_residual(n, 0, y%polaramv(n)%u(k), &
30                                       oi%polaramv(n)%u(k), n_obs_bad % u)
31             re%polaramv(n)%v (k)= da_residual(n, 0, y%polaramv(n)%v(k), &
32                                    oi%polaramv(n)%v(k), n_obs_bad % v)            
33         end do
34      end do
35       
36      np_missing = np_missing + n_obs_bad % u % num % miss + &
37                    n_obs_bad % v % num % miss
38      np_bad_data = np_bad_data + n_obs_bad % u % num % bad + &
39                     n_obs_bad % v % num % bad
40      np_obs_used = np_obs_used + n_obs_bad % u % num % use + &
41                     n_obs_bad % v % num % use
42 
43    end if
44 
45 end subroutine da_residual_polaramv
46 
47