Time of emergence of rainfall signals in Ecuador: code, derived data and GIS layers

Code, derived data, GIS layers and figures supporting the study "When does the rainfall signal emerge from natural variability? Time of emergence and the uncertainty from reference data and bias correction for rainfall extremes in Andean, Amazonian and coastal Ecuador". The study evaluates the time of emergence (ToE) of rainfall signals (annual rainfall, dry-season rainfall, consecutive dry days and annual maximum daily rainfall) in the EPMAPS territory (Quito), in Coast, Austro and Amazon contexts (INAMHI gauges) and in continental Ecuador (404 NEX-GDDP-CMIP6 cells), together with the evaluation of CHIRPS v2/v3 and of bias-correction methods for NEX-GDDP-CMIP6. Contents- 01_code: Python scripts of the three analyses and shared modules. Scripts contain absolute paths of the authors' computer; edit ROOT at the top of each script.- 02_derived_data: annual maxima, station inventories, CHIRPS evaluation, bias-correction results, projected change factors, time-of-emergence tables for every route, and annual NEX-GDDP-CMIP6 indicators per cell.- 03_gis: shapefiles and GeoPackage (EPSG:32717): isohyets, change and uncertainty isolines, zones, stations, NEX cells with change and time of emergence.- 04_figures: figures of the paper (English, 300 dpi) and maps in Spanish. Data sources (not redistributed in full): EPMAPS rain gauges (ParamH2O portal, https://paramh2o.aguaquito.gob.ec/); INAMHI daily series (public information; only derived annual maxima are included); CHIRPS v2/v3 (Climate Hazards Center, https://doi.org/10.15780/G2JQ0P); NASA NEX-GDDP-CMIP6 (Thrasher et al., 2022), accessed through Google Earth Engine; administrative limits from FAO GAUL 2015; roads and places from OpenStreetMap contributors (ODbL). Licences: data, tables, figures and GIS layers, CC BY 4.0; code, MIT. Note: results are scenario-conditional ranges, not probabilities. A time of emergence that is absent before 2090 does not imply the absence of change.