:orphan: .. role:: underline :class: underline WRF Overview ============ | The WRF model is a flexible, state-of-the-art atmospheric simulation system that is portable and efficient on parallel computing platforms. It is suitable for use across scales, ranging from meters to thousands of kilometers, for a broad range of applications, including the following. | .. csv-table:: :header: "Research Applications", "Functional Applications" :widths: 30, 30 :width: 75% "Parameterization", "Idealized simulations" "Data assimilation", "Real-time numerical weather prediction" "Forecasting", "Model coupling" "Tropical cyclones", "Teaching" "Regional climate" "Fire" | | | .. rst-class:: horizbuttons-primary-m * `Access the latest WRF code`_ | | | .. image:: ../../images/users_guide/wrf_system_flow_chart.png :width: 800px :align: left :height: 600px | | | | The WRF Modeling System consists of the following programs. * :ref:`WRF Preprocessing System` (WPS) * :ref:`WRF Initialization` Programs (Real and Ideal) * :ref:`WRF-ARW Solver` (WRF) * :ref:`WRF Data Assimilation` (WRFDA) * :ref:`Post-processing, Analysis, and Visualization Tools` | | | .. _WRF Preprocessing System: WRF Preprocessing System (WPS) ------------------------------ The WPS is used for real-data simulations and functions to: #. define simulation domains #. interpolate terrestrial data (e.g., terrain, landuse, and soil types) to the simulation domain #. degrib and horizontally interpolate meteorological input data from an outside model to the simulation domain | | | .. _WRF Initialization: WRF Initialization ------------------ The WRF model is capable of simulating both **real-data** and **idealized** cases. | .. _Real-data Cases: Real-data Cases +++++++++++++++ .. container:: row m-0 p-0 .. container:: col-md-12 pl-0 pr-3 py-3 m-0 .. container:: card px-0 h-100 .. rst-class:: card-header-def .. rubric:: Real-data Case .. container:: card-body-def A model simulation that uses real static geographical data (e.g., landuse) from reputable surveying projects, along with a previously-run external atmospheric analysis or forecast model (e.g., GFS) to provide initial and boundary conditions for the WRF simulation | The :ref:`WRF Preprocessing System` processes the input atmospheric and static fields and interpolates them to a user-defined domain. WPS output files are used as input to the WRF's *real.exe* initialization program. | | .. _Idealized Cases: Idealized Cases +++++++++++++++ .. container:: row m-0 p-0 .. container:: col-md-12 pl-0 pr-3 py-3 m-0 .. container:: card px-0 h-100 .. rst-class:: card-header-def .. rubric:: Idealized Case .. container:: card-body-def A model simulation of an "idealized," simplified, and controlled environment | Idealized simulations are initiated from an an existing sounding (included with the code), and assume a simplified orography. Idealized simulations can provide the following: * Basic testing of the dynamics solver for a broad range of space and time scales * Reproducing known solutions * A starting point/template for other idealized experiments * Testing physics development | `See WRF Initialization`_ for details about available cases. | | | .. _WRF-ARW Solver: WRF-ARW Solver -------------- The *wrf.exe* program is the primary component of the modeling system. | Key Features ++++++++++++ * Fully-compressible nonhydrostatic equations with a hydrostatic option * Complete Coriolis and curvature terms * Mass-based hybrid sigma-pressure vertical coordinate * Map-scale factors for these projections: * Polar Stereographic (conformal) * Lambert-conformal * Mercator (conformal) * Latitude and longitude, which can be rotated * Arakawa C-grid staggering * Scalar-conserving flux form for prognostic variables * Upper boundary absorption and Rayleigh damping * Lateral boundary conditions * Idealized cases: periodic, symmetric, and open radiative * Real cases: specified with relaxation zone * Full physics options for land-surface, planetary boundary layer, atmospheric and surface radiation, microphysics and cumulus convection * Orographic gravity wave drag | | Additional Options ++++++++++++++++++ * Regional and global applications * Two-way nesting with multiple nests and nest levels * Concurrent one-way nesting with multiple nests and nest levels * Offline one-way nesting with vertical nesting * Moving nests (prescribed moves and vortex tracking) * Vertical grid-spacing can vary with height * Runge-Kutta 2nd and 3rd order time integration options * 2nd to 6th order advection options (horizontal and vertical) * Monotonic transport and positive-definite advection option for moisture, scalar, tracer, and TKE * Weighted Essentially Non-Oscillatory (WENO) advection option * Time-split small step for acoustic and gravity-wave modes: * Small step horizontally explicit, vertically implicit * Divergence damping option and vertical time off-centering * External-mode filtering option * Ocean models * Grid analysis nudging using separate upper-air and surface data, and observation nudging * Spectral nudging * Digital filter initialization * Adaptive time stepping * Stochastic parameterization schemes * A number of idealized examples | | | .. _WRF Data Assimilation: WRF Data Assimilation (WRFDA) ----------------------------- .. important:: WRFDA Notice, 20230901: NSF-NCAR/MMM no longer has a dedicated staff for supporting and developing WRFDA. While WRFDA will continue to be maintained, NSF-NCAR/MMM has primarily transitioned to the development of an MPAS data assimilation system based upon the Joint Effort for Data Assimilation Integration (JEDI), i.e., MPAS-JEDI. NSF-NCAR/MMM is working to develop the supporting materials and platform for MPAS-JEDI and offers MPAS-JEDI tutorials. | WRF Data Assimilation (WRFDA) is an optional program used to ingest observations into interpolated analysis created by WPS. It may also be used to update the WRF model's initial conditions by running in "cycling" mode. WRFDA's primary features are: * The capability of 3D and 4D hybrid data assimilation (Variational + Ensemble) * Based on an incremental variational data assimilation technique * Tangent linear and adjoint of WRF are fully integrated with WRF for 4D-Var * Utilizes the conjugate gradient method to minimize cost function in the analysis control variable space * Analysis on an un-staggered Arakawa A-grid * Analysis increments interpolated to staggered Arakawa C-grid, which is then added to the background (first guess) to get the final analysis of the WRF-model grid * Conventional observation data input may be supplied in either ASCII format via the *obsproc* utility, or *PREPBUFR* format * Multiple-satellite observation data input may be supplied in BUFR format * Two fast radiative transfer models, CRTM and RTTOV, are interfaced to WRFDA to serve as satellite radiance observation operator * Variational bias correction for satellite radiance data assimilation * All-sky radiance data assimilation capability * Multiple radar data (reflectivity & radial velocity) input is supplied through ASCII format * Multiple outer loop to address nonlinearity * Capability to compute adjoint sensitivity * Horizontal background (first guess) error is represented via a recursive filter (for regional) or power spectrum (for global) * Vertical background error is applied through projections on climatologically-generated, averaged eigenvectors and its corresponding Eigen values * Horizontal and vertical background errors are non-separable. Each eigenvector has its own horizontal climatologically-determined length scale * Preconditioning of the background of the cost function is done via the control variable transform U defined as B=UUT * *gen_be* utility to generate climatological background error covariance estimate via the NMC-method or ensemble perturbations * Utility program to update WRF boundary condition file after WRF-DA | | | .. _Post-processing, Analysis, and Visualization Tools: Post-processing, Analysis, and Visualization Tools -------------------------------------------------- The following post-processing programs are supported for use with WRF output. * wrf-python_ A collection of diagnostic and interpolation routines for use with output from the WRF model * NCL_ (NCAR Command Language) A free, interpreted language designed specifically for scientific data processing and visualization. NCL has robust file input and output. It can read in netCDF, HDF4, HDF4-EOS, GRIB, binary and ASCII data. The graphics are world-class and highly customizable. * RIP_ (Read/Interpolate/Plot) A Fortran program that invokes NCAR Graphics routines for the purpose of visualizing output from gridded meteorological data sets, primarily from mesoscale numerical models * **ARWpost** A package that reads-in WRF-ARW model data and creates GrADS output files. * UPP_ (Unified Post Processing) A system deleveloped at the National Centers for Environmental Prediction (NCEP) and is used operationally for models maintained by NCEP. It is currently supported by the Research Applications Laboratory (RAL) at NSF NCAR. * VAPOR_ (Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers) A 3-dimensional data visualization tool developed and supported by the VAPOR team at NSF NCAR (vapor at ucar dot edu) * METplus_ (Model Evaluation Tools) A verification system developed and supported by the Developmental Testbed Center at NSF NCAR (met_help at ucar dot edu). | Details of these programs (with the exception of METplus) are included in `WRF Post-processing`_ and , `WRF Utilities and Tools`_. | | | Resources --------- `WRF Users Website`_ `WRF Tutorial Presentations`_ `WRF-ARW Tech Note`_ `WRF Online Tutorial`_ `WRF Compiling Tutorial`_ `How to Cite WRF`_ `WRF Support Forum`_ | | | | | .. rst-class:: horizbuttons-next-m * `Next: Compiling ->`_ .. _`How to Cite WRF`: https://www2.mmm.ucar.edu/wrf/users/citing_wrf.html .. _METplus: http://www.dtcenter.org/met/users/ .. _NCL: http://www.ncl.ucar.edu/ .. _`WRF Post-processing`: ./post_processing.html .. _`WRF Utilities and Tools`: ./utilities_tools.html .. _RIP: https://www2.mmm.ucar.edu/wrf/users/docs/ripug.htm .. _UPP: https://ral.ucar.edu/solutions/products/unified-post-processor-upp .. _VAPOR: http://www.vapor.ucar.edu/ .. _`WRF-ARW Tech Note`: https://www2.mmm.ucar.edu/wrf/users/docs/technote/contents.html .. _`WRF Compiling Tutorial`: https://www2.mmm.ucar.edu/wrf/OnLineTutorial/compilation_tutorial.php .. _`Access the latest WRF code`: https://github.com/wrf-model/WRF/releases .. _`WRF Online Tutorial`: https://www2.mmm.ucar.edu/wrf/OnLineTutorial/index.php .. _wrf-python: https://wrf-python.readthedocs.io/en/latest/ .. _`WRF Support Forum`: https://forum.mmm.ucar.edu/phpBB3/ .. _`WRF Tutorial Presentations`: http://www2.mmm.ucar.edu/wrf/users/tutorial/tutorial.html .. _`WRF Users Website`: https://www2.mmm.ucar.edu/wrf/users/ .. _`Next: Compiling ->`: ./compiling.html .. _`See WRF Initialization`: ./initialization.html | | | .. toctree:: :maxdepth: 4 :hidden: foreword.rst self compiling.rst WPS Real-data Init. Idealized Init. running_wrf.rst dynamics.rst physics.rst namelist_variables.rst output.rst troubleshooting.rst Software/Computation Post-processing utilities_tools.rst WRFDA fire.rst