Package: BLRPM 1.0
Christoph Ritschel
BLRPM: Stochastic Rainfall Generator Bartlett-Lewis Rectangular Pulse Model
Due to a limited availability of observed high-resolution precipitation records with adequate length, simulations with stochastic precipitation models are used to generate series for subsequent studies [e.g. Khaliq and Cunmae, 1996, <doi:10.1016/0022-1694(95)02894-3>, Vandenberghe et al., 2011, <doi:10.1029/2009WR008388>]. This package contains an R implementation of the original Bartlett-Lewis rectangular pulse model (BLRPM), developed by Rodriguez-Iturbe et al. (1987) <doi:10.1098/rspa.1987.0039>. It contains a function for simulating a precipitation time series based on storms and cells generated by the model with given or estimated model parameters. Additionally BLRPM parameters can be estimated from a given or simulated precipitation time series. The model simulations can be plotted in a three-layer plot including an overview of generated storms and cells by the model (which can also be plotted individually), a continuous step-function and a discrete precipitation time series at a chosen aggregation level.
Authors:
BLRPM_1.0.tar.gz
BLRPM_1.0.tar.gz(r-4.5-noble)BLRPM_1.0.tar.gz(r-4.4-noble)
BLRPM_1.0.tgz(r-4.4-emscripten)BLRPM_1.0.tgz(r-4.3-emscripten)
BLRPM.pdf |BLRPM.html✨
BLRPM/json (API)
# Install 'BLRPM' in R: |
install.packages('BLRPM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:6d39a6ae9e. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
Exports:BL.accBL.simBL.stepfunBLRPM.estBLRPM.simTS.accTS.stats
Dependencies:R6