da_residual_profiler.inc

1 subroutine da_residual_profiler(oi, y, re,                        &
2                                         np_missing, np_bad_data,          &
3                                         np_obs_used, np_available)
4 
5    !-----------------------------------------------------------------------
6    ! Purpose: Calculate residuals for profilers
7    !-----------------------------------------------------------------------
8 
9    implicit none
10 
11    type (ob_type), intent(in)        :: oi     ! Innovation vector (O-B).
12    type (y_type) , intent(in)        :: y      ! y = H (xa)
13    type (y_type) , intent(inout)     :: re     ! Residual structure.
14 
15    integer       , intent(inout)     :: np_available, np_obs_used,          &
16                                         np_missing  , np_bad_data
17 
18    type (bad_data_type)              :: n_obs_bad
19    integer                           :: n, k
20 
21    if (oi%num_Profiler > 0) then
22 
23       n_obs_bad % u % num = number_type(0, 0, 0)
24       n_obs_bad % v % num = number_type(0, 0, 0)
25 
26       do n=1, oi%num_Profiler
27 
28          do k=1, oi%Profiler(n)%info%levels
29 
30             np_available = np_available + 2
31 
32             re%Profiler(n)%u(k) = da_residual(n, k, y%Profiler(n)%u(k), &
33                                       oi%Profiler(n)%u(k), n_obs_bad % u)
34             re%Profiler(n)%v(k) = da_residual(n, k, y%Profiler(n)%v(k), &
35                                       oi%Profiler(n)%v(k), n_obs_bad % v)
36          end do
37       end do
38 
39       np_missing = np_missing + n_obs_bad % u % num % miss + &
40                    n_obs_bad % v % num % miss
41       np_bad_data = np_bad_data + n_obs_bad % u % num % bad + &
42                     n_obs_bad % v % num % bad 
43       np_obs_used = np_obs_used + n_obs_bad % u % num % use + &
44                     n_obs_bad % v % num % use
45    end if
46 
47 end subroutine da_residual_profiler
48 
49