diff --git a/CHANGELOG.rst b/CHANGELOG.rst index 88d3e888a4..bf819884e3 100644 --- a/CHANGELOG.rst +++ b/CHANGELOG.rst @@ -22,6 +22,15 @@ individual files. The changes are now listed with the most recent at the top. +**December 1 2023 :: Bringing DART documentation in accordance with NSF Policy. Tag v10.9.2** + +- doc-fixes: + + - Brings DART documentation in accordance with the November 2023, + "Official Policy on Brand Standards of the U.S. National Science + Foundation." Changes instances of "NCAR" to "NSF NCAR" and adds + NSF logo to the DART logo in the navigation menu. + **November 9 2023 :: Github Actions MPIf08 Check. Tag v10.9.1** - Adds a new check to the Github Actions workflow that uses the diff --git a/assimilation_code/modules/assimilation/adaptive_inflate_mod.rst b/assimilation_code/modules/assimilation/adaptive_inflate_mod.rst index e6ad6e18d3..1bf2ef36af 100644 --- a/assimilation_code/modules/assimilation/adaptive_inflate_mod.rst +++ b/assimilation_code/modules/assimilation/adaptive_inflate_mod.rst @@ -9,7 +9,7 @@ It can provide constant valued inflation in state or observation space, consiste provide spatially-constant, time-varying adaptive inflation. It can provide spatially-varying, time-varying adaptive inflation and it can provide temporally-varying observation space inflation. And finally, it can provide adaptive damped inflation, which decreases inflation through time when observation density varies. Diagnostic output and restart files -are available. Several papers on the NCAR `DART `__ website document the +are available. Several papers on the NSF NCAR `DART `__ website document the algorithms in detail. The ``DART/tutorial/section12`` chapter has more information. Details on controlling the inflation options are contained in the documentation for the filter. The filter_nml controls diff --git a/conf.py b/conf.py index e32e4edc7b..29904ab3a6 100644 --- a/conf.py +++ b/conf.py @@ -17,11 +17,11 @@ # -- Project information ----------------------------------------------------- project = 'DART' -copyright = '2022, University Corporation for Atmospheric Research' +copyright = '2023, University Corporation for Atmospheric Research' author = 'Data Assimilation Research Section' # The full version, including alpha/beta/rc tags -release = '10.9.1' +release = '10.9.2' root_doc = 'index' # -- General configuration --------------------------------------------------- @@ -71,7 +71,7 @@ # html_theme = 'sphinx_rtd_theme' html_show_sphinx = False -html_logo = 'guide/_static/ncar-dart-logo-navy.svg' +html_logo = 'guide/_static/nsf-ncar-dart.png' html_theme_options = { 'logo_only': True, 'includehidden': False diff --git a/guide/_static/ncar-dart-logo-navy.svg b/guide/_static/ncar-dart-logo-navy.svg deleted file mode 100644 index 34337dadae..0000000000 --- a/guide/_static/ncar-dart-logo-navy.svg +++ /dev/null @@ -1,43 +0,0 @@ - - - - -NCAR-contemp-logo-blue.a - - - - - - - - - - - - - diff --git a/guide/_static/nsf-ncar-dart.png b/guide/_static/nsf-ncar-dart.png new file mode 100644 index 0000000000..4b8709192b Binary files /dev/null and b/guide/_static/nsf-ncar-dart.png differ diff --git a/guide/available-observation-converters.rst b/guide/available-observation-converters.rst index 123a488215..6b84da9cae 100644 --- a/guide/available-observation-converters.rst +++ b/guide/available-observation-converters.rst @@ -59,8 +59,8 @@ In addition the following external program produces DART observation sequence files: - `Observation Processing And Wind Synthesis - (OPAWS) `__: OPAWS can process NCAR Dorade - (sweep) and NCAR EOL Foray (netCDF) radar data. It analyzes (grids) data in + (OPAWS) `__: OPAWS can process NSF NCAR Dorade + (sweep) and NSF NCAR EOL Foray (netCDF) radar data. It analyzes (grids) data in either two-dimensions (on the conical surface of each sweep) or three-dimensions (Cartesian). Analyses are output in netCDF, Vis5d, and/or DART (Data Assimilation Research Testbed) formats. diff --git a/guide/benefits-of-using-dart.rst b/guide/benefits-of-using-dart.rst index 31b1b20b72..8eb653fd13 100644 --- a/guide/benefits-of-using-dart.rst +++ b/guide/benefits-of-using-dart.rst @@ -66,7 +66,7 @@ Here are some of the many benefits of using DART: functionality, so for this purpose it is best to first get in touch with the DART team at dart @ ucar.edu to make the process as smooth as possible. 7. Finally, and perhaps most importantly, DART **has world-class support** - available from the DART team at NCAR. A talented team of dedicated software + available from the DART team at NSF NCAR. A talented team of dedicated software engineers and data assimilation scientists work together to continually improve DART and support user needs. See the `About page `__ for more information about the DART team. diff --git a/guide/brief-history-of-dart.rst b/guide/brief-history-of-dart.rst index 5dd0588cf2..cdbe4a0db8 100644 --- a/guide/brief-history-of-dart.rst +++ b/guide/brief-history-of-dart.rst @@ -2,7 +2,7 @@ A brief history of DART ======================= The DART project was initiated in August 2001, and in 2003, the Data -Assimilation Research Section (DAReS) was officially formed at NCAR. In 2004, +Assimilation Research Section (DAReS) was officially formed at NSF NCAR. In 2004, the first officially supported version of DART was released. Consistent version control history is available back to 2005, making DART an extremely long-lived and well-supported software project. Since 2004, there have been more than a diff --git a/guide/creating-obs-seq-real.rst b/guide/creating-obs-seq-real.rst index 0564a04c2b..4233cb06da 100644 --- a/guide/creating-obs-seq-real.rst +++ b/guide/creating-obs-seq-real.rst @@ -114,7 +114,7 @@ Data sources and formats See the various subdirectories here, which generally include information on where the example data was obtained and in what format it is distributed. Most data is available for download off the web. The Data Support Section (DSS) at -NCAR has large data repositories, the MADIS data center distributes observations +NSF NCAR has large data repositories, the MADIS data center distributes observations in netCDF format, GTS real-time weather data is available from various sources. For new converters, if you can find what format the data is distributed in you may be able to adapt one of the existing converters here for your own use. diff --git a/index.rst b/index.rst index f69b1c0aff..389e223bea 100644 --- a/index.rst +++ b/index.rst @@ -6,8 +6,8 @@ Welcome to the Data Assimilation Research Testbed The Data Assimilation Research Testbed (DART) is an open-source, freely available community facility for ensemble data assimilation (DA). [1]_ DART is developed and maintained by the `Data Assimilation Research Section -(DAReS) `_ at the `National Center -for Atmospheric Research (NCAR) `_. +(DAReS) `_ at the NSF `National Center +for Atmospheric Research (NSF NCAR) `_. +------------------------------+------------------------------+ | |spaghetti_square| | |assim_anim| | diff --git a/models/POP/readme.rst b/models/POP/readme.rst index 438754f450..6ece91e7fa 100644 --- a/models/POP/readme.rst +++ b/models/POP/readme.rst @@ -13,7 +13,7 @@ of POP: (CESM POP2; Smith et al. 2010 [1]_). This document also provides `Detailed instructions for using DART and CESM POP2 -on NCAR's supercomputer`_, including information about the availability of +on NSF NCAR's supercomputer`_, including information about the availability of restart files for `Creating an initial ensemble`_ of model states and `Observation sequence files`_ for assimilation. @@ -30,7 +30,7 @@ In years subsequent to the initial development of the DART interface, the Computer, Computational, and Statistical Sciences Division at LANL transitioned from using POP as their primary ocean model to using the Model for Prediction Across Scales-Ocean (MPAS-Ocean). Thus it became difficult for staff in the -Data Assimilation Research Section (DAReS) at NCAR to maintain access to the +Data Assimilation Research Section (DAReS) at NSF NCAR to maintain access to the `LANL POP `_ source code. As a result, LANL POP has been tested using DART's Lanai framework but has not been tested using DART's Manhattan framework. If you intend to use @@ -40,10 +40,10 @@ dart@ucar.edu. CESM POP2 ~~~~~~~~~ -The NCAR implementation of POP, `CESM POP2 +The NSF NCAR implementation of POP, `CESM POP2 `_, has been used -extensively with DART throughout multiple generations of NCAR's supercomputer -(Bluefire, Yellowstone & Cheyenne) and multiple iterations of NCAR's earth +extensively with DART throughout multiple generations of NSF NCAR's supercomputer +(Bluefire, Yellowstone & Cheyenne) and multiple iterations of NSF NCAR's earth system model (CCSM4, CESM1 and CESM2). CESM POP2 is supported under DART's Manhattan framework. @@ -52,24 +52,24 @@ to manage the ensemble and the Flux Coupler is responsible for stopping POP2 at the times required to perform an assimilation. CESM runs continuously and all of the DART routines run at each assimilation time. -Detailed instructions for using DART and CESM POP2 on NCAR's supercomputer --------------------------------------------------------------------------- +Detailed instructions for using DART and CESM POP2 on NSF NCAR's supercomputer +------------------------------------------------------------------------------ -If you're using NCAR's supercomputer, you can run the setup scripts after +If you're using NSF NCAR's supercomputer, you can run the setup scripts after making minor edits to set details that are specific to your project. The setup scripts create a CESM case in which POP is configured using a 1° horizontal grid, and uses the eddy parametrization of Gent and McWilliams (1990). [2]_ The CICE model is active and atmospheric forcing is provided by the `CAM6 DART Reanalysis `_. -The filesystem attached to NCAR's supercomputer is known as the Globally +The filesystem attached to NSF NCAR's supercomputer is known as the Globally Accessible Data Environment (GLADE). All filepaths on GLADE have the structure: .. code-block:: /glade/* -If you aren't using NCAR's supercomputer, take note of when the ``/glade/`` +If you aren't using NSF NCAR's supercomputer, take note of when the ``/glade/`` filepath is present in the setup scripts, since this will indicate sections that you must alter in order to get the scripts to work on your supercomputer. Additionally, you'll need to generate your own initial condition and @@ -80,7 +80,7 @@ staff by emailing dart@ucar.edu for assistance. Summary ------- -To use DART and CESM POP2 on NCAR's supercomputer, you will need to complete +To use DART and CESM POP2 on NSF NCAR's supercomputer, you will need to complete the following steps. #. Configure the scripts for your specific experiment by editing @@ -134,8 +134,8 @@ access to this directory by CISL. Use the `Service Desk you're unable to get permission, contact DAReS staff for assistance by emailing dart@ucar.edu. -Filepaths beginning with ``/glade/campaign/*`` can't be accessed from NCAR's -supercomputer nodes. You must log on to NCAR's data visualization computer to +Filepaths beginning with ``/glade/campaign/*`` can't be accessed from NSF NCAR's +supercomputer nodes. You must log on to NSF NCAR's data visualization computer to copy files from ``/glade/campaign/*``. This python script was created by *Dan Amrhein*. Thanks Dan! @@ -147,13 +147,13 @@ This python script was created by *Dan Amrhein*. Thanks Dan! | | g210.G_JRA.v14.gx1v7.01 experiment that are saved in | | | campaign storage. You must be granted access to the CGD | | | Ocean Section campaign storage directory and be logged on | -| | to NCAR's data visualization computer in order to run | +| | to NSF NCAR's data visualization computer in order to run | | | this script. The assignment of the ``stagedir`` variable | | | in this script should match the assignment of the | | | ``stagedir`` variable in ``DART_params.csh``. | +-------------------------------+-----------------------------------------------------------+ -In order to use this script, log in to NCAR's data visualization computer and +In order to use this script, log in to NSF NCAR's data visualization computer and use python to run the script. For example: .. code-block:: @@ -420,7 +420,7 @@ References .. [1] Smith, R., and Coauthors, 2010: The Parallel Ocean Program (POP) Reference Manual Ocean Component of the Community Climate System Model - (CCSM) and Community Earth System Model (CESM). National Center for + (CCSM) and Community Earth System Model (CESM). NSF National Center for Atmospheric Research, `http://www.cesm.ucar.edu/ models/cesm1.0/pop2/doc/sci/POPRefManual.pdf `_. diff --git a/models/cam-fv/readme.rst b/models/cam-fv/readme.rst index 7eec3b32cb..c47683c2b8 100644 --- a/models/cam-fv/readme.rst +++ b/models/cam-fv/readme.rst @@ -21,7 +21,7 @@ An interface to MPAS is being developed (contact us about the current status). The flexibility of the DART environment has led to its use by graduate students, post-graduates, and scientists at universities and research labs to conduct data assimilation research. Others are using the -products of data assimilation (analyses), which were produced here at NCAR +products of data assimilation (analyses), which were produced at NSF NCAR using CESM+DART, to conduct related research. The latest reanalysis is described in the DART |CAM6_Rean|_ @@ -117,14 +117,14 @@ Reanalyses There have been two large-scale reanalysis efforts using CAM-FV and DART. The **CAM6 Data Assimilation Research Testbed (DART) Reanalysis** -is archived in the NCAR Research Data Archive +is archived in the NSF NCAR Research Data Archive `DS345.0 `__ . (See the |CAM6_Rean|_ ). It contains just under 120Tb (yes Tb) of data: These CAM6+DART Reanalysis data products are designed to facilitate a broad variety of research using - NCAR's CESM2 models, ranging from model evaluation to (ensemble) + NSF NCAR's CESM2 models, ranging from model evaluation to (ensemble) hindcasting (initial conditions), data assimilation experiments, and sensitivity studies. They come from an 80 member ensemble reanalysis of the global troposphere and stratosphere using CAM6-FV from CESM2.1. @@ -138,7 +138,7 @@ It contains just under 120Tb (yes Tb) of data: An earlier, more limited dataset can be found in the `**Ensemble of Atmospheric Forcing Files from a CAM4-FV Reanalysis** `__ -is archived in the NCAR Research Data Archive +is archived in the NSF NCAR Research Data Archive `DS199.1 `__ . It contains about 1.5Tb of data: @@ -147,7 +147,7 @@ It contains about 1.5Tb of data: Research Testbed (DART) using the Community Atmosphere Model Version 4 with the finite volume core (CAM4-FV) at 1.9 degree by 2.5 degree resolution. The observations assimilated include all those used in - the NCEP/NCAR reanalysis (temperature and wind components from + the NCEP/NSF NCAR reanalysis (temperature and wind components from radiosondes, aircraft, and satellite drift winds) plus radio occultation observations from the COSMIC satellites starting in late 2006. These files are intended to be used as 'DATM stream files' @@ -164,13 +164,13 @@ The CAM6+DART Reanalysis used "observation sequence files" which contain the types of observations in the table below ("T" = temperature, "U" = zonal wind, "V" = meridional wind, "Q" = specific humidity, "refractivity" = the bending of light by density variations). -These files are available on NCAR's glade file system: +These files are available on NSF NCAR's glade file system: /glade/p/cisl/dares/Observations/NCEP+ACARS+GPS+AIRS/Thinned_x9x10. Versions of these files, which also have the results of the reanalysis in them, are available from the RDA ds345.0 linked above. NCEP - NCEP's PREPBUFR files (prepqm) in NCAR's Research Data Archive: + NCEP's PREPBUFR files (prepqm) in NSF NCAR's Research Data Archive: (https://rda.ucar.edu/datasets/ds090.0/) COSMIC diff --git a/models/clm/tutorial/README.rst b/models/clm/tutorial/README.rst index 15da268757..08d6c4570e 100644 --- a/models/clm/tutorial/README.rst +++ b/models/clm/tutorial/README.rst @@ -114,7 +114,7 @@ custom initial conditions and observation sequence files for your own work. .. Important :: - We have provided tutorial instructions for the NCAR + We have provided tutorial instructions for the NSF NCAR supercomputer Cheyenne, however, if using your own machine you will need to customize the setup scripts in order to properly compile DART (see Step 4: Compiling DART). These system-specific setup steps may take a good deal of @@ -144,7 +144,7 @@ Step 1: Download CLM5 --------------------- CLM is continually being updated by the model developer and user community -consisting of both NCAR and university scientists and researchers. +consisting of both NSF NCAR and university scientists and researchers. In contrast, DART is maintained by a relatively small group that supports numerous earth system models (20+) including CLM. Therefore the DART team focuses on only supporting official released versions of CLM. This documentation @@ -186,7 +186,7 @@ SourceMods see the main :doc:`CLM-DART documentation. <../readme>` Compiling CLM5 -------------- -Compiling CLM5 on the NCAR machine Cheyenne is straightforward because the +Compiling CLM5 on the NSF NCAR machine Cheyenne is straightforward because the run and build environment settings are already defined within the ``config_machines.xml`` file located within the CESM installation: ``/cime/config/cesm/machines``. If you are using your own machine please follow the porting instructions located diff --git a/models/cm1/readme.rst b/models/cm1/readme.rst index 58026d048f..432b2618b4 100644 --- a/models/cm1/readme.rst +++ b/models/cm1/readme.rst @@ -9,8 +9,8 @@ non-hydrostatic numerical model in Cartesian 3D coordinates designed for the study of micro-to-mesoscale atmospheric phenomena in idealized to semi-idealized simulations. -The CM1 model was developed and is maintained by George Bryan at the National -Center for Atmospheric Research (NCAR) Mesoscale and Microscale Meteorology +The CM1 model was developed and is maintained by George Bryan at the NSF National +Center for Atmospheric Research (NSF NCAR) Mesoscale and Microscale Meteorology Laboratory (MMM). The model code is freely available from the `CM1 website `_ diff --git a/models/mpas_atm/readme.rst b/models/mpas_atm/readme.rst index d6c0a2c537..30da79678f 100644 --- a/models/mpas_atm/readme.rst +++ b/models/mpas_atm/readme.rst @@ -452,7 +452,7 @@ Compilation The DART interface for MPAS-ATM can be compiled with various fortran compilers such as (but not limited to) gfortran, pgf90, and intel. It has been tested on a -Mac and NCAR IBM supercomputer (yellowstone). +Mac and NSF NCAR IBM supercomputer (yellowstone). .. note:: diff --git a/models/tiegcm/readme.rst b/models/tiegcm/readme.rst index 2cf30ffd8d..4fb4c42659 100644 --- a/models/tiegcm/readme.rst +++ b/models/tiegcm/readme.rst @@ -8,7 +8,7 @@ Overview -------- The Thermosphere Ionosphere Electrodynamic General Circulation Model -(`TIEGCM `__) is developed by the NCAR +(`TIEGCM `__) is developed by the NSF NCAR High Altitude Observatory (`HAO `__). diff --git a/models/wrf/tutorial/README.rst b/models/wrf/tutorial/README.rst index e0be016ec1..90d3295048 100644 --- a/models/wrf/tutorial/README.rst +++ b/models/wrf/tutorial/README.rst @@ -63,8 +63,8 @@ observations will then be performed at 06:00 UTC, at which time analysis files will be generated to begin a new ensemble forecast. The WRF model will be advanced for 6 hours and a final assimilation cycle will be performed at 12:00 UTC. This process could then continue in order to -investigate the strong rain and wind event. For what it’s worth, on -NCAR’s *Cheyenne* under the default test configuration for this case, it +investigate the strong rain and wind event. For what it's worth, on +NSF NCAR's *Cheyenne* under the default test configuration for this case, it can take an hour to complete a forecast/assimilation cycle. Since the tutorial runs for two cycles, it can take twice as long. @@ -75,14 +75,14 @@ However, you will need to do additional work before you can expect to have a fully functional WRF/DART system, as some of the steps involved in this tutorial (in particular, the perturbation bank and the observation sequence files) are provided for you in order to simplify -the process. Furthermore, if you are not running on the UCAR/NCAR +the process. Furthermore, if you are not running on the NSF NCAR Cheyenne supercomputing system, you will likely need to customize the assimilation scripts to match the details of your particular system. .. important :: - We have provided instructions for the NCAR supercomputer + We have provided instructions for the NSF NCAR supercomputer Cheyenne, so you may need to tailor these instructions to your system if you are not using Cheyenne. These system-specific setup steps may take a good deal of effort, especially if you are unfamiliar with details such @@ -632,15 +632,15 @@ To (again, *optionally*) reproduce the observation sequence files in the ./quickbuild.sh - Download the PREPBUFR observations for your desired time. Go to the - `NCAR/UCAR Research Data + `NSF NCAR Research Data Archive `__ page for the - NCEP/NCAR Global Reanalysis Products. Register on the site, click on + NCEP/NSF NCAR Global Reanalysis Products. Register on the site, click on the "Data Access" tab, and follow either the instructions for - external users or NCAR internal users. + external users or NSF NCAR internal users. - The downloaded *.tar* file will often be COS-blocked. If so, the file will appear corrupted if you attempt to untar it without converting - the data. See the `NCAR COS-block `__ + the data. See the `NSF NCAR COS-block `__ page for more information on how to strip the COS-blocking off of your downloaded file. @@ -837,7 +837,7 @@ scripts is necessary to glue all of the pieces together. A set of scripts is provided with the tutorial tarball to provide you a starting point for your own WRF/DART system. You will need to edit these scripts, perhaps extensively, to run them within your particular computing -environment. If you will run on NCAR's Cheyenne environment, fewer edits +environment. If you will run on NSF NCAR's Cheyenne environment, fewer edits may be needed, but you should familiarize yourself with `running jobs on Cheyenne `__ if necessary. A single forecast/assimilation cycle of this tutorial can @@ -951,7 +951,7 @@ In some cases there could be multiple obs_epoch*.nc files, but in general, the u should use the obs_epoch file appended with the largest numeric value as it contains the most complete set of observations. The diagnostic scripts used here are included within the DART package, and require a license of Matlab to run. The -commands shown below to run the diagnostics use NCAR's Cheyenne, but a user could +commands shown below to run the diagnostics use NSF NCAR's Cheyenne, but a user could also run on their local machine. First explore the obs_epoch*.nc file and identify the variety of observations included diff --git a/models/wrf_hydro/readme.rst b/models/wrf_hydro/readme.rst index 70dc8b59ee..721d763450 100644 --- a/models/wrf_hydro/readme.rst +++ b/models/wrf_hydro/readme.rst @@ -12,8 +12,8 @@ simulate land surface processes. Combined with DART, the facility is called *HydroDART*. The development of HydroDART was a collaboration between **James McCreight** -of the Research Applications Laboratory of NCAR and **Moha Gharamti** of -the Data Assimilation Research Section of NCAR. +of the Research Applications Laboratory of NSF NCAR and **Moha Gharamti** of +the Data Assimilation Research Section of NSF NCAR. Streamflow assimilation is an active area of research and provides many interesting research challenges. diff --git a/observations/obs_converters/AIRS/convert_airs_L2.rst b/observations/obs_converters/AIRS/convert_airs_L2.rst index 85d86cdf4c..5703a5985a 100644 --- a/observations/obs_converters/AIRS/convert_airs_L2.rst +++ b/observations/obs_converters/AIRS/convert_airs_L2.rst @@ -111,7 +111,7 @@ would be *lon1 = 300, lon2 = 40, lat1 = -60, lat2 = -30*. The ``DART/observations/obs_converters/AIRS/shell_scripts`` directory includes scripts (``download_L2.sh`` and ``oneday_down.sh``) that make use of the fact that the AIRS data -is also archived on the NCAR HPSS (tape library) in daily tar files. +is also archived on the NSF NCAR HPSS (tape library) in daily tar files. ``oneday_down.sh`` has options to download a day of granule files, convert them, merge them into daily files, and remove the original data files and repeat the process for any specified time period. diff --git a/observations/obs_converters/GSI2DART/readme.rst b/observations/obs_converters/GSI2DART/readme.rst index 3c8e521b50..1b16a29f10 100644 --- a/observations/obs_converters/GSI2DART/readme.rst +++ b/observations/obs_converters/GSI2DART/readme.rst @@ -5,7 +5,7 @@ Overview -------- The GSI2DART converter was contributed by **Craig Schwartz** and **Jamie Bresch** of the -Mesoscale & Microscale Meteorology Lab at NCAR. *Thanks Craig and Jamie!* +Mesoscale & Microscale Meteorology Lab at NSF NCAR. *Thanks Craig and Jamie!* This converter is designed to convert observation files created by the Gridpoint Statistical Interpolation (GSI) system maintained by the National Oceanic and diff --git a/observations/obs_converters/MPD/README.rst b/observations/obs_converters/MPD/README.rst index 803e5fdc1f..11a2ce7c16 100644 --- a/observations/obs_converters/MPD/README.rst +++ b/observations/obs_converters/MPD/README.rst @@ -24,4 +24,4 @@ https://www.image.ucar.edu/pub/DART/MPD/MPD.tar.gz For more details of the retrieval and quality control process, and inquire about data availability for your research project, please -contact Tammy Weckwerth at EOL, NCAR. +contact Tammy Weckwerth at EOL, NSF NCAR. diff --git a/observations/obs_converters/NCEP/prep_bufr/prep_bufr.rst b/observations/obs_converters/NCEP/prep_bufr/prep_bufr.rst index 5349692096..5b6b0aa022 100644 --- a/observations/obs_converters/NCEP/prep_bufr/prep_bufr.rst +++ b/observations/obs_converters/NCEP/prep_bufr/prep_bufr.rst @@ -70,7 +70,7 @@ This package is currently organized into files under the DART/observations/NCEP/ install.sh A script to install the NCEP PREPBUFR decoder and the NCEP BUFR library. exe Executables of the decoder and converter. data Where the NCEP PREPBUFR files (prepqm****) could be loaded into - from the NCAR Mass Store (the script assumes this is the default location). + from the NSF NCAR Mass Store (the script assumes this is the default location). work Where we run the script to do the decoding. convert_bufr Source code (grabbufr) to convert the binary big-endian PREPBUFR files to little-endian files, and a script to compile the program. @@ -145,15 +145,15 @@ executable cwordsh.x executable. Note that if you can get the blocked file formats to begin with, this program is not needed. -Getting the ncep reanalysis prepbufr format data from ncar hpss -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +Getting the ncep reanalysis prepbufr format data from NSF NCAR HPSS +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -The NCEP PREPBUFR files (prepqmYYMMDDHH) can be found within the NCEP reanalysis dataset, ds090.0, on NCAR Mass Store +The NCEP PREPBUFR files (prepqmYYMMDDHH) can be found within the NCEP reanalysis dataset, ds090.0, on NSF NCAR Mass Store System (HPSS). To find the files: -- go to the `NCAR/NCEP reanalysis archive. `__ +- go to the `NSF NCAR/NCEP reanalysis archive. `__ - Click on the "Inventories" tab. - Select the year you are interested in. - Search for files with the string "prepqm" in the name. @@ -166,7 +166,7 @@ A21902. After September 2003, these files include AIRCRAFT data (airplane readin ACARS data (airplane readings taken during takeoff and landing). There are different datasets which include ACARS data but their use is restricted and you must contact the RDA group to get access. -| If you are running on a machine with direct access to the NCAR HPSS, then change directories into the prep_bufr/data +| If you are running on a machine with direct access to the NSF NCAR HPSS, then change directories into the prep_bufr/data subdirectory and run: | *> hsi get /DSS/A##### rawfile* | where ##### is the data set number you want. @@ -178,7 +178,7 @@ but their use is restricted and you must contact the RDA group to get access. | *> mv rawfile data.tar* | *> tar -xvf data.tar* | However, if you get an error from the tar command you will need to run the ``cosconvert`` program to convert the file - into a readable tar file. On the NCAR machine *yellowstone*, run: + into a readable tar file. On the NSF NCAR machine *yellowstone*, run: | *> /glade/u/home/rdadata/bin/cosconvert -b rawfile data.tar* | On other platforms, download the appropriate version from: http://rda.ucar.edu/libraries/io/cos_blocking/utils/ . Build and run the converter and then you should have a tar file you can unpack. diff --git a/observations/obs_converters/README.rst b/observations/obs_converters/README.rst index 24a7d9ad13..0425020a93 100644 --- a/observations/obs_converters/README.rst +++ b/observations/obs_converters/README.rst @@ -61,7 +61,7 @@ Data Sources and Formats See the various subdirectories here, which generally include information on where the example data was obtained and in what format it is distributed. Most data is available for download off the web. The Data -Support Section (DSS) at NCAR has large data repositories, the MADIS +Support Section (DSS) at NSF NCAR has large data repositories, the MADIS data center distributes observations in NetCDF format, GTS real-time weather data is available from various sources. For new converters, if you can find what format the data is distributed in you may be able to @@ -406,8 +406,8 @@ In addition the following external program produces DART observation sequence files: - `Observation Processing And Wind Synthesis - (OPAWS) `__: OPAWS can process NCAR - Dorade (sweep) and NCAR EOL Foray (netcdf) radar data. It analyzes + (OPAWS) `__: OPAWS can process NSF NCAR + Dorade (sweep) and NSF NCAR EOL Foray (netcdf) radar data. It analyzes (grids) data in either two-dimensions (on the conical surface of each sweep) or three-dimensions (Cartesian). Analyses are output in netcdf, Vis5d, and/or DART (Data Assimilation Research Testbed) diff --git a/observations/obs_converters/WOD/WOD.rst b/observations/obs_converters/WOD/WOD.rst index ab373bbf61..97c66d25fd 100644 --- a/observations/obs_converters/WOD/WOD.rst +++ b/observations/obs_converters/WOD/WOD.rst @@ -34,7 +34,7 @@ Data sources Use already existing obs_seq files ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -NCAR staff have prepared datasets already converted to DART's obs_seq file +NSF NCAR staff have prepared datasets already converted to DART's obs_seq file format for the World Ocean Database 2013 (WOD13) and the World Ocean Database 2009 (WOD09). @@ -45,7 +45,7 @@ format for the World Ocean Database 2013 (WOD13) and the World Ocean Database | PSU = g/kg | MSU = PSU/1000 = kg/kg - The WOD observation sequence files availiable from NCAR's RDA are in MSU. + The WOD observation sequence files availiable from NSF NCAR's RDA are in MSU. WOD13 ~~~~~ @@ -101,10 +101,10 @@ Download WOD from NCEI Data from each of the WOD releases can be downloaded interactively from the `WOD website `__. -Download WOD from NCAR -^^^^^^^^^^^^^^^^^^^^^^ +Download WOD from NSF NCAR +^^^^^^^^^^^^^^^^^^^^^^^^^^ -WOD09 can also be downloaded from NCAR's `research data archive (RDA) dataset +WOD09 can also be downloaded from NSF NCAR's `research data archive (RDA) dataset 285.0 `__. Programs diff --git a/observations/obs_converters/gps/gps.rst b/observations/obs_converters/gps/gps.rst index 650e14b088..2f018a51e2 100644 --- a/observations/obs_converters/gps/gps.rst +++ b/observations/obs_converters/gps/gps.rst @@ -342,7 +342,7 @@ If you are converting only a day or two of observations you can download the fil programs from the command line. However if you are going convert many days/months/years of data you need an automated script, possibly submitted to a batch queue on a large machine. The following instructions describe shell scripts we provide as a guide in the ``shell_scripts`` directory. You will have to adapt them for your own system unless you are -running on an NCAR superscomputer. +running on an NSF NCAR supercomputer. | **Making DART Observations from Radio Occultation atmPrf Profiles:** @@ -424,7 +424,7 @@ running on an NCAR superscomputer. | -| **Notes on already converted observations on the NCAR supercomputers** +| **Notes on already converted observations on the NSF NCAR supercomputers** | **GPS Radio Occultation Data:** :: diff --git a/observations/obs_converters/radar/README.rst b/observations/obs_converters/radar/README.rst index 7b251e3475..7a1a5c85f9 100644 --- a/observations/obs_converters/radar/README.rst +++ b/observations/obs_converters/radar/README.rst @@ -48,7 +48,7 @@ Real radar observations Once you have ensured that your data are quality controlled, use the `Observation Processing And Wind Synthesis (OPAWS) `__ utility convert your data to `obs_seq` format. The OPAWS utility reads specific -types of files as input, such as DORADE sweep files and NCAR EOL Foray data. +types of files as input, such as DORADE sweep files and NSF NCAR EOL Foray data. OPAWS analyzes and grids data in either: