Git Product home page Git Product logo

Comments (1)

timhoar avatar timhoar commented on September 6, 2024 1

Thank you for your interest in DART. We offer limited support for the conversion of radar observations to the DART observation format. Still, there are avenues that can allow you to get there. As an end goal, you'll want to have radar observations that have been quality controlled to remove non-meteorological scatterers and other artifacts, and reduce the native data resolution to something closer to twice the expected horizontal grid spacing in your model (e.g., with 3 km grid spacing, radar observations every 6 km) interpolated along the sweep plane. Reflectivity observations are often partitioned into two types - regular reflectivity observations, and clear air reflectivity observations (where no radar echoes are observed). Quality control is best done with the raw data, so I trust you have an ability to do so on your end. Once quality control is applied, a tool for the interpolation and conversion to DART observation format is provided by the OPAWS utility: https://code.google.com/archive/p/opaws/

Before you can use the OPAWS tool, you'll need to convert your native data format into something that can be read by OPAWS (e.g., DORADE sweep files). You can see if the RADX utility is helpful for this: https://ral.ucar.edu/projects/titan/docs/radial_formats/radx.html

Assuming you are using WRF, you'll need to make some code modifications to allow for forward operator calculations. For reflectivity, most of the available microphysics schemes have built in capability to output reflectivity, assuming a 10-cm wavelength. If you are not using an S-band radar, be aware that attenuation is not accounted for in the built-in reflectivity operator. For radial velocity, you'll need to also generate a new diagnostic field, terminal fall velocity. There is very limited support for fall velocity in WRF, although it is partially supported in the Thompson microphysics scheme (though you would still need to modify WRF code to get this diagnostic output to history files). With these two fields available in your WRF history files, you can add them to your DART wrf_state_variables list and should be ready to assimilate radar observations. Before assimilating radar observations, you'll also want to use special localization for radar observations, typically 12-24 km. If you leave range-folding in your radar observations, you'll need to build the special version of DART that unfolds the velocity observations on-the-fly.

from dart.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.