Welcome to RASCAL’s documentation!
RASCAL is a python library desinged to reconstruct time series of climatological data, based on the Analog Method (AM), to use them for climate studies. The AM is a statistical downscalling method, based on the assumption that large-scale atmospheric conditions tend to produce similar local weather patterns, and therefore is possible to predict local conditions finding analog days, with similar large-scale patterns, in the historical record. The objective of RASCAL is to generate complete time series, based on limited observational data, that can reproduce the climatic characteristics of the region to study better than the reanalysis products.
Indices and tables
Contents
- Getting Started
- Begginer Tutorials
- Advanced Tutorials
- Code Overview: Modules
- analogs.py
- analysis.py
rascal.analysis.RSkill
rascal.analysis.RSkill.observations
rascal.analysis.RSkill.reconstructions
rascal.analysis.RSkill.reanalysis
rascal.analysis.RSkill.data
rascal.analysis.RSkill.resample()
rascal.analysis.RSkill.plotseries()
rascal.analysis.RSkill.skill()
rascal.analysis.RSkill.taylor()
rascal.analysis.RSkill.annual_cycle()
rascal.analysis.RSkill.qqplot()
- indices.py
rascal.analysis.CIndex
rascal.analysis.CIndex.fd()
rascal.analysis.CIndex.su()
rascal.analysis.CIndex.id()
rascal.analysis.CIndex.tr()
rascal.analysis.CIndex.gsl()
rascal.analysis.CIndex.txx()
rascal.analysis.CIndex.tnx()
rascal.analysis.CIndex.txn()
rascal.analysis.CIndex.tnn()
rascal.analysis.CIndex.tn10p()
rascal.analysis.CIndex.tx10p()
rascal.analysis.CIndex.tn90p()
rascal.analysis.CIndex.tx90p()
rascal.analysis.CIndex.wsdi()
rascal.analysis.CIndex.csdi()
rascal.analysis.CIndex.dtr()
rascal.analysis.CIndex.rx1day()
rascal.analysis.CIndex.rx5day()
rascal.analysis.CIndex.sdii()
rascal.analysis.CIndex.r10mm()
rascal.analysis.CIndex.r20mm()
rascal.analysis.CIndex.rnnmm()
rascal.analysis.CIndex.cdd()
rascal.analysis.CIndex.cwd()
rascal.analysis.CIndex.r95ptot()
rascal.analysis.CIndex.r99ptot()
rascal.analysis.CIndex.prcptot()