quantile-mapping

A collection of bias correction techniques written in Python - for climate sciences.

Climate Data Bias Corrector: A tool to bias correct the Global Climate Model (GCM)/ Regional Climate Model (RCM) simulated future climatic daily projections.

Bias correction command-line tool for climatic research written in C++

Preprocessing Scripts for VIC-CropSyst Modeling

Reproduction and QM/QDM extension of a CMIP6-based assessment of future photovoltaic and wind-energy potential over China.

Reproducible pipeline for the integrated downscaling–BMA–BiLSTM framework: CMIP6 GCM evaluation, two-track downscaling (LARS-WG 8 + DQM), EM-based Bayesian Model Averaging, deep-ensemble streamflow projection, and drought / ETCCDI / compound-extreme analysis. Demonstrated on the Haraz basin, northern Iran.

Performmance/execution time test of the bias correction tool BiasAdjustCXX v1.8 in comparison to python-cmethods v0.6.1 and xclim v0.40.0.

Code to Bias Correct ICAR output based on Livneh data, using quantile mapping.

ROI-agnostic Python framework fusing quantile-harmonised Landsat C2L2 SR/ST and Sentinel-2 L2A stacks, spatially blocked RF/GBDT surface-state inference with TreeSHAP, Hamed-Rao MK / Theil-Sen / PELT change diagnostics, robust-z LST anomalies with LISA, and Sentinel-1 SBAS (HyP3-MintPy) kinematic attribution.

Fetch account details from Plaid API and create a pie chart on spending. Plan for retirement based on Monte Carlo simulation assuming normal PDE for 30 years on 4% withdrawals