Giter VIP home page Giter VIP logo

calalti's People

Contributors

yangleir avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

calalti's Issues

Correction of the Dry PD for geoid height

To validate the satellite radiometer wet PD though GNSS measurement, one should make the wet PD from two sources at the same height. Otherwise, there will have system bias between GNSS and satellite radiometers (could be several cm for 100 m height difference).
The dry PD is necessary to calculate the wet PD from GNSS. Three sources could be used to estimate the Dry PD:

    1. GNSS atmospheric pressure loading models
    1. ECMWF model from satellite GDR
    1. ERA5 of ECMWF

At present, the GNSS source is the most simple and convenient, which is provided by the GNSS processing results. The ERA5 maybe kind of hard, because you need to download lots of pressure data (not difficult, but lots of work). The ECMWF model from satellite GDR is another good and easy choice, since dry PD is already in the GDR. However, the dry PD from GDR is referred to the sea surface height, and there need a correction due to height.

If set the dry PD source to GDR data, the program still lacks the correction due to height difference between GNSS sites and mean sea surface height.
The main procedures for using dry PD from GDR include:

  • Retrieve the pressure from GDR dry PD through Saastamoinen model (at mean sea surface height).
  • Correct the pressure due to height variation between GNSS and MSS. (not finish)
  • Re-calculate the dry PD at GNSS height with corrected pressure.

At present, I missed the step 2. So the validation result will be significantly affected if the height variation is large (100 m).

But, the result will be ok if use the dry PD from GNSS model. (The accuracy maybe little decreased).

The program needs to be improved is (line 75-90): https://github.com/GenericAltimetryTools/CalAlti/blob/master/src/wet_inter.m

First try

The help files need to be improved.

Recommend Projects

  • React photo React

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

  • Vue.js photo Vue.js

    ๐Ÿ–– 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. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

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 โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.