edrewitz/WxData: WxData 2.3 Released

WxData 2.3 (C) Eric J. Drewitz 2025-2026 Documentation And Examples WxData Documentation and Examples What's New? Several new end-to-end data clients to download and process model data from the Canadian Meteorological Centre (CMC) Canadian Global Deterministic Prediction System (GDPS) Canadian Regional Deterministic Prediction System (RDPS) Canadian High Resolution Deterministic Prediction System (HRDPS) Canadian Global Ensemble Prediction System (GEPS) Canadian Seasonal to Inter-annual Prediction System (CanSIPS) Forecasts Canadian Seasonal to Inter-annual Prediction System (CanSIPS) Hindcasts from wxdata.model_data.cmc.gdps.gdps import gdps from wxdata.model_data.cmc.rdps.rdps import rdps from wxdata.model_data.cmc.hrdps.hrdps import hrdps from wxdata.model_data.cmc.geps.geps import geps from wxdata.model_data.cmc.cansips.forecast.cansips_forecast import cansips_forecast from wxdata.model_data.cmc.cansips.hindcast.cansips_hindcast import cansips_hindcast Important Note The cansips_hindcast() client automates the methodology described here to create a 30-year climatology in order to compute forecast anomalies. CanSIPS Hindcast Methodology TLDR Beginning at the current month, download the hindcast for all forecast steps from month 0 (current month) through month 11 (12 steps total) for each year from 1991-2020. Create an xarray.array for each year of hindcast data. Combine these datasets into one xarray.array. Create an xarray.array of the ensemble mean between all 40 ensemble members of the combined dataset. Improvements Nothing at this time. Bug Fixes Nothing at this time.