Changes between Version 6 and Version 7 of pyPDAF

Timestamp:

Jun 12, 2025, 2:26:34 PM (5 days ago)

Author:

lnerger

Comment:

--

pyPDAF

@@ -13 +13 @@
 The Fortran implementation of data assimilation systems is used  with various regional and global models of Earth system components, including atmosphere, ocean, hydrology, land surface and sea ice models. These models are typically written in Fortran which can be easily used with PDAF. When PDAF's online-coupling is used, data assimilation with these models is more natually implemented in Fortran. Still one can use pyPDAF efficiently for the offline mode of PDAF. 
 
-The interface inherits the efficiency of the data assimilation algorithms in Fortran, and the flexibility to be applied to different models and observations. This means that users of pyPDAF can couple the DA algorithms with any types of model and observations without the need to coding the actual DA algorithms. This allows the users to focus on the specific research problems. pyPDAF supports all DA methods provided by PDAF, thus many variants of ensemble Kalman filters, particle filters and other non-linear filters. It also provides variants of 3DVar. A full list of supported methods can be found on the [wiki:FeaturesofPdaf Page on Feature of PDAF].
+pyPDAF inherits the efficiency of the data assimilation algorithms of PDAF coded in Fortran, and the flexibility to be applied to different models and observations. This means that users of pyPDAF can couple the DA algorithms with any types of model and observations without the need to coding the actual DA algorithms. This allows the users to focus on the specific research problems. pyPDAF supports all DA methods provided by PDAF, thus many variants of ensemble Kalman filters, particle filters and other non-linear filters. It also provides variants of 3DVar. A full list of supported methods can be found on the [wiki:FeaturesofPdaf Page on Features of PDAF].
 
 pyPDAF was developed by Yumeng Chen at the University of Reading and the National Center for Earth Observation (NCEO) in the United Kingdom.