manually updating to master ... use git log --follow

Updating Manhattan to correct the PR44/45 debacle now that the
master branch is ready to be released as 9.9.0
The debacle was a merge to the wrong branch and immediately reverted,
however, the revert had unintended consequences.

.gitignore

@@ -13,7 +13,9 @@ _site/
 # Nuisance files
 
 # Makefile
+build_templates/mkmf.template
 dart_log.*
+mkmf.template
 input.nml.*default
 filter_ics
 obs_def_mod.f90
@@ -23,6 +25,11 @@ check_me.nc
 check_me_interptest.*
 *.orig
 
+# RTTOV coefficient files
+
+mietable*
+rtcoef*
+
 # Executables
 
 advance_time
@@ -54,6 +61,7 @@ perturb_single_instance
 preprocess
 restart_file_tool
 system_simulation
+rttov_test
 
 # Directories to NOT IGNORE ... same as executable names
 # as far as I know, these must be listed after the executables

COPYRIGHT.md

@@ -1,5 +1,5 @@
 
-![DARTlogo](documentation/images/Dartboard7.png "DART Logo")
+![DARTlogo](docs/images/Dartboard7.png "DART Logo")
 
 Copyright 2019 University Corporation for Atmospheric Research
 

README.md

@@ -3,20 +3,16 @@
 
 ## Welcome to DART, the Data Assimilation Research Testbed.
 
-[quick-start instructions for the impatient](#QuickStart)
-
 Extensive on-line documentation is available at the GitHub project web pages:
 [https://dart.ucar.edu/](https://dart.ucar.edu/)
-or in the repository at [docs/index.md](docs/index.md). It's probably a good idea
-to be familiar with the [GitHub flow](https://guides.github.com/introduction/flow/).
+or in the GitHub [repository](docs/). Quick-start instructions for the impatient can be found [below](#QuickStart), while more detailed setup instructions and other topics such as a brief introduction to data assimilation, the history of DART, etc. are covered in the 
+[DART Getting Started Guide](https://dart.ucar.edu/pages/Getting_Started.html). 
 
 <table><tr>
 <td><img height=250, src="./docs/images/DARTspaghettiSquare.gif"></td> 
 <td><img height=250, src="./docs/images/science_nuggets/AssimAnim.gif"></td>
 </tr></table>
 
-[Extensive local documentation is included with DART.](docs/index.md)
-
 A Matlab-based introduction is in the `docs/DART_LAB` directory.  
 There are a set of PDF presentations along with hands-on Matlab exercises.  
 This starts with a very basic introduction to data assimilation and covers 
@@ -88,6 +84,13 @@ Update the DART version and year as appropriate.
 <a name="QuickStart"></a>
 ## Quick-start for the impatient:
 
+1. fork the NCAR/DART repo
+1. clone your (new) fork to your machine - this will set up a remote named 'origin'
+1. create a remote to point back to the NCAR/DART repo ... convention dictates that this remote should be called 'upstream'
+1. check out the appropriate branch
+1. Download one of the tar files (listed below) of 'large' files so you can test your DART installation.
+1. If you want to issue a PR, create a feature branch and push that to your fork and issue the PR.
+
 There are several large files that are needed to run some of the tests and examples but are not included
 in order to keep the repository as small as possible. If you are interested in running *bgrid_solo*, 
 *cam-fv*, or testing the *NCEP/prep_bufr* observation converter, you will need these files.

assimilation_code/modules/assimilation/filter_mod.f90

@@ -1,8 +1,6 @@
 ! DART software - Copyright UCAR. This open source software is provided
 ! by UCAR, "as is", without charge, subject to all terms of use at
 ! http://www.image.ucar.edu/DAReS/DART/DART_download
-!
-! $Id$
 
 module filter_mod
 
@@ -101,10 +99,9 @@ module filter_mod
           filter_main
 
 ! version controlled file description for error handling, do not edit
-character(len=256), parameter :: source   = &
-   "$URL$"
-character(len=32 ), parameter :: revision = "$Revision$"
-character(len=128), parameter :: revdate  = "$Date$"
+character(len=*), parameter :: source   = 'filter_mod.f90'
+character(len=*), parameter :: revision = ''
+character(len=*), parameter :: revdate  = ''
 
 ! Some convenient global storage items
 character(len=512)      :: msgstring
@@ -1674,8 +1671,11 @@ subroutine obs_space_diagnostics(obs_fwd_op_ens_handle, qc_ens_handle, ens_size,
 
 ! allocate temp space for sending data only on the task that will
 ! write the obs_seq.final file
-if (my_task == io_task) allocate(obs_temp(num_obs_in_set))
-
+if (my_task == io_task) then
+   allocate(obs_temp(num_obs_in_set))
+else ! TJH: this change became necessary when using Intel 19.0.5 ...
+   allocate(obs_temp(1))
+endif
 
 ! Update the ensemble mean
 call get_copy(io_task, obs_fwd_op_ens_handle, OBS_MEAN_START, obs_temp)
@@ -1721,7 +1721,7 @@ subroutine obs_space_diagnostics(obs_fwd_op_ens_handle, qc_ens_handle, ens_size,
    end do
 endif
 
-if (my_task == io_task) deallocate(obs_temp)
+deallocate(obs_temp)
 
 end subroutine obs_space_diagnostics
 
@@ -2043,18 +2043,22 @@ subroutine create_ensemble_from_single_file(ens_handle)
 
 type(ensemble_type), intent(inout) :: ens_handle
 
-integer               :: i ! loop variable
+integer               :: i
 logical               :: interf_provided ! model does the perturbing
 logical, allocatable  :: miss_me(:)
+integer               :: partial_state_on_my_task ! the number of elements ON THIS TASK
 
 ! Copy from ensemble member 1 to the other copies
 do i = 1, ens_handle%my_num_vars
    ens_handle%copies(2:ens_size, i) = ens_handle%copies(1, i)  ! How slow is this?
 enddo
 
-! store missing_r8 locations
-if (get_missing_ok_status()) then ! missing_r8 is allowed in the state
-   allocate(miss_me(ens_size))
+! If the state allows missing values, we have to record their locations
+! and restore them in all the new perturbed copies.
+
+if (get_missing_ok_status()) then
+   partial_state_on_my_task = size(ens_handle%copies,2)
+   allocate(miss_me(partial_state_on_my_task))
    miss_me = .false.
    where(ens_handle%copies(1, :) == missing_r8) miss_me = .true.
 endif
@@ -2064,11 +2068,12 @@ subroutine create_ensemble_from_single_file(ens_handle)
    call perturb_copies_task_bitwise(ens_handle)
 endif
 
-! Put back in missing_r8
+! Restore the missing_r8
 if (get_missing_ok_status()) then
    do i = 1, ens_size
       where(miss_me) ens_handle%copies(i, :) = missing_r8
    enddo
+   deallocate(miss_me)
 endif
 
 end subroutine create_ensemble_from_single_file
@@ -2724,26 +2729,22 @@ subroutine test_obs_copies(obs_fwd_op_ens_handle, information)
 character(len=*),    intent(in) :: information
 
 character(len=20)  :: task_str !! string to hold the task number
-character(len=129) :: file_obscopies !! output file name
-integer :: i
+character(len=256) :: file_obscopies !! output file name
+integer :: i, iunit
 
 write(task_str, '(i10)') obs_fwd_op_ens_handle%my_pe
 file_obscopies = TRIM('obscopies_' // TRIM(ADJUSTL(information)) // TRIM(ADJUSTL(task_str)))
-open(15, file=file_obscopies, status ='unknown')
+
+iunit = open_file(file_obscopies, 'formatted', 'append')
 
 do i = 1, obs_fwd_op_ens_handle%num_copies - 4
-   write(15, *) obs_fwd_op_ens_handle%copies(i,:)
+   write(iunit, *) obs_fwd_op_ens_handle%copies(i,:)
 enddo
 
-close(15)
+close(iunit)
 
 end subroutine test_obs_copies
 
 !-------------------------------------------------------------------
 end module filter_mod
 
-! <next few lines under version control, do not edit>
-! $URL$
-! $Id$
-! $Revision$
-! $Date$