Releases: CSU-Radarmet/CSU_RadarTools
CSU_RadarTools v1.4
Version 1.4 of CSU_RadarTools
Python tools for polarimetric radar retrievals.
This codebase was developed at Colorado State University by numerous people, including Brenda Dolan, Brody Fuchs, Kyle Wiens, Rob Cifelli, Larry Carey, Timothy Lang, and others.
Currently, fuzzy-logic-based hydrometeor identification, blended rainfall, DSD retrievals, and liquid/ice mass calculations are supported. There is also an algorithm that uses a finite impulse response (FIR) filter to process differential phase and calculate specific differential phase. Finally, there are some tools to do rudimentary QC on the data.
These are supplied as standalone functions that take polarimetric radar data as arguments. Scalars and arrays are supported as function inputs. The main exception is csu_kdp.calc_kdp_bringi() which requires individual rays, sweeps, or volumes of radar data.
This version includes numerous code cleanup and improvements.
CSU_RadarTools v1.3
Version 1.3 of CSU_RadarTools
Python tools for polarimetric radar retrievals.
This codebase was developed at Colorado State University by numerous people, including Brenda Dolan, Brody Fuchs, Kyle Wiens, Rob Cifelli, Larry Carey, Timothy Lang, and others.
Currently, fuzzy-logic-based hydrometeor identification, blended rainfall, DSD retrievals, and liquid/ice mass calculations are supported. There is also an algorithm that uses a finite impulse response (FIR) filter to process differential phase and calculate specific differential phase. Finally, there are some tools to do rudimentary QC on the data.
These are supplied as standalone functions that take polarimetric radar data as arguments. Scalars and arrays are supported as function inputs. The main exception is csu_kdp.calc_kdp_bringi() which requires individual rays, sweeps, or volumes of radar data.
This version includes numerous code cleanup and improvements to enable binary packaging via pip/conda
CSU_RadarTools v1.2
Version 1.2 of CSU_RadarTools
Python tools for polarimetric radar retrievals.
This codebase was developed at Colorado State University by numerous people, including Brenda Dolan, Brody Fuchs, Kyle Wiens, Rob Cifelli, Larry Carey, Timothy Lang, and others.
Currently, fuzzy-logic-based hydrometeor identification, blended rainfall, DSD retrievals, and liquid/ice mass calculations are supported. There is also an algorithm that uses a finite impulse response (FIR) filter to process differential phase and calculate specific differential phase. Finally, there are some tools to do rudimentary QC on the data.
These are supplied as standalone functions that take polarimetric radar data as arguments. Scalars and arrays are supported as function inputs. The main exception is csu_kdp.calc_kdp_bringi() which requires individual rays, sweeps, or volumes of radar data.
CSU_RadarTools v1.2a
Version 1.2 of CSU_RadarTools
Python tools for polarimetric radar retrievals.
This codebase was developed at Colorado State University by numerous people, including Brenda Dolan, Brody Fuchs, Kyle Wiens, Rob Cifelli, Larry Carey, Timothy Lang, and others.
Currently, fuzzy-logic-based hydrometeor identification, blended rainfall, DSD retrievals, and liquid/ice mass calculations are supported. There is also an algorithm that uses a finite impulse response (FIR) filter to process differential phase and calculate specific differential phase. Finally, there are some tools to do rudimentary QC on the data.
These are supplied as standalone functions that take polarimetric radar data as arguments. Scalars and arrays are supported as function inputs. The main exception is csu_kdp.calc_kdp_bringi() which requires individual rays, sweeps, or volumes of radar data.