{ "created_utc": "2026-10-12T12:26:58.473651+00:00", "config": "config/bias_correction/feb_fmam.json", "config_contents": { "schema_version": 1, "name": "feb_fmam", "description": "Rainfall-amount bias-correction benchmark: February-initialized ECMWF SEAS5, FMAM season and its calendar months, every 0.25 deg cell of Ethiopia (docs/47).", "cycle": "config/cycles/feb_2026_fmam.json", "project_config": "config/fmam_feb/project.json", "targets": [ "Feb", "Mar", "Apr", "May", "FMAM" ], "training_years": [ 1993, 2016 ], "test_years": [ 2017, 2025 ], "all_years": [ 1993, 2025 ], "forecast_year": 2026, "cells": { "path": "data/masks/ethiopia_common.nc", "variable": "region_mask" }, "regions": { "ethiopia": { "label": "All Ethiopia", "path": "data/masks/ethiopia_common.nc", "variable": "region_mask" }, "fmam_domain": { "label": "FMAM rainfall contribution domain", "path": "data/masks/fmam_coverage_chirps_v3_1993_2025_v1.nc", "variable": "season_domain" } }, "primary_region": "ethiopia", "reference_method": "mvs", "smoothing_alpha": 0.5, "dry_threshold_mm": 1.0, "pit_bins": 10, "methods": { "raw": {}, "ls": { "min_model_mean": 0.1 }, "mvs": { "ratio_bounds": [ 0.5, 2.0 ], "min_model_sd": 1.0 }, "vs": { "ratio_bounds": null, "min_model_sd": 1.0 }, "sqrt_mvs": { "ratio_bounds": [ 0.5, 2.0 ], "min_model_sd": 0.1, "space": "sqrt" }, "pt": { "b_bounds": [ 0.1, 3.0 ] }, "dc": { "ratio_bounds": [ 0.2, 5.0 ], "min_model_mean": 0.1 }, "loci": { "wet_threshold": 1.0 }, "eqm": { "extrapolation": "constant_ratio", "wet_threshold": 1.0 }, "gqm": { "wet_threshold": 1.0 }, "dqm": { "extrapolation": "constant_ratio", "ratio_bounds": [ 0.2, 5.0 ], "min_model_mean": 0.1, "wet_threshold": 1.0 }, "qdm": { "max_ratio": 5.0, "wet_threshold": 1.0 }, "sdm": { "wet_threshold": 1.0 }, "cdft": { "min_model_mean": 0.1 }, "mvs_zero_guard": { "ratio_bounds": [ 0.5, 2.0 ], "min_model_sd": 1.0, "zero_guard": true } }, "example_cell_quantiles": [ 0.1, 0.5, 0.9 ], "confirmation": { "methods": [ "mvs", "ls", "vs", "sqrt_mvs", "pt", "dc", "loci", "eqm", "gqm", "dqm", "qdm", "sdm", "cdft" ], "variants": [ "mvs_zero_guard" ], "selection_region": "ethiopia", "reliability_bins": 10, "reliability_methods": [ "mvs", "sqrt_mvs", "gqm", "eqm" ], "output_root": "outputs/bias_correction_benchmark/feb_fmam/confirmation" }, "output_root": "outputs/bias_correction_benchmark/feb_fmam" }, "provenance": { "commit": "9f397927f5d4ddf2be3a1fa52595f34fc8fcb56a", "uncommitted_changes": false, "code_sha256": { "scripts/bias_methods.py": "03b2fdd8a645b96f27e4087a96408c0b412b135c80bfc23637757c6c44f9c370", "scripts/bias_benchmark.py": "b2cbc28349379aa016ef81d0255ac9edd21b38ffc5425b9a12c93a1df52e9084", "scripts/bias_confirmation.py": "f2fd9f9c0a73d3ed54e670f7770b47139793173cbdcd42dda1ba642be90848cc", "scripts/significance.py": "3143761d5d201e4e62df9ad923757b952a3ea768b060c8a722afcd9b3d6a9963", "scripts/calibration_core.py": "f0635cc563e6d6aedb62799847b83fbb0f5cc12ee9f8c48ad48dda15a054fb62", "scripts/compare_calibration.py": "9aa137c9a02672ffacc2541cfd23cdab9b3294bf7cc77580a11e21208560866a", "scripts/local_blend.py": "ada5c571fb7762d2c333f83ad119d35f0784b82aa2cc35449a44cdf00c53c17d", "scripts/run_calibration.py": "1f34e8fc92fdd15983f1633de67fcb6a35882911b6b7072ca865df99d907afd0", "scripts/run_monthly.py": "dc13dfb54b78773afb6d0c25ebac8769552e5c071f5d2aed9ba2a01400e44f79", "scripts/cycle.py": "00e076fc93dc2c8a5caebf6a209fc3de09a5f69e16c2e7cb20bd7b36d2ecdcba", "scripts/common.py": "72b83f5c530017e317ea43af3a0e430e6d03f361bc032de374a0f942435cb0a1" }, "config": { "path": "config/bias_correction/feb_fmam.json", "sha256": "5e74d282f6e0f984a3bb2d0527f665d535894be91f139628db7e8deb7d5374c9" }, "project_config": { "path": "config/fmam_feb/project.json", "sha256": "9999e9e5e03f95998e3d22396d2d2e5bf2f8c79decfc571c715caf2878daa4a1" }, "cycle_config": { "path": "config/cycles/feb_2026_fmam.json", "sha256": "120955984a14d292912b9a8d48f83af060290d40d6b54ed9d627b36280c0652b" }, "masks": { "cells": { "path": "data/masks/ethiopia_common.nc", "sha256": "57ad8861c598abb9f175012920e5d0ef058e5b643cd6e4987cad3da6ac0b9e16" }, "ethiopia": { "path": "data/masks/ethiopia_common.nc", "sha256": "57ad8861c598abb9f175012920e5d0ef058e5b643cd6e4987cad3da6ac0b9e16" }, "fmam_domain": { "path": "data/masks/fmam_coverage_chirps_v3_1993_2025_v1.nc", "sha256": "c386d127f7041ed6b383c5f46b9537e3740bfee6b85f383e3a8b0792cac58fbb" } }, "inputs": { "Feb": { "folder": "data/processed/init02_Feb", "files": 67, "sha256": "aa05fc058f64121f726ee7f06608768bafb243ef9702ccd6c154217f2a9a13d5" }, "Mar": { "folder": "data/processed/init02_Mar", "files": 67, "sha256": "41b2c07eb813ed00ca81d1c21d2a620cd1cdbc2d2725e806669bd035f1a8f7cf" }, "Apr": { "folder": "data/processed/init02_Apr", "files": 67, "sha256": "7c29ca912e693cabdd2d1626e106f967dd554116d18f98a18faa33f957dfb15e" }, "May": { "folder": "data/processed/init02_May", "files": 67, "sha256": "c590b53da737506d77661bb04aa6caf2a91d62a0ab9b88d8a2ecbb7c49b925c0" }, "FMAM": { "folder": "data/processed/init02_FMAM", "files": 67, "sha256": "6915035b5cc71c72bb89702c935f922163818566aa3868159a9183f7326db742" } }, "scoring_version": 3, "dependency_sha256": "fe51e7585ac5c768040f758353565a1b438e5069af37ebb9541ef385ab323fdb", "python": "3.11.9", "numpy": "1.26.4" }, "protocol": "Benchmark rainfall-amount bias-correction methods member by member, for every grid cell and target (docs/47).\n\nRead-only experiment: never touches the operational forecasts. Configured by config/bias_correction/.json.\n\nDesigns (one score per year: area-weighted over a region; years weighted equally):\n training : leave-one-year-out within the training years; the scored year never enters a fit (clean; screened)\n operational : fit on the training years, scored on the test years (exploratory; these years were seen before)\n full : leave-one-year-out within all observed years, for per-cell maps and distribution checks (descriptive)\n forecast : fit on all observed years, corrected forecast-year members of every method (member-by-member comparison)\nScores: ensemble CRPS (mm) of the empirical distribution delivered to users and its CRPSS against the CHIRPS training\nclimatology (primary); the fair CRPS (Ferro 2014) as a separately labelled diagnostic; ensemble-mean bias, MAE, RMSE\nand correlation; spread-error ratio; rank histograms; tercile RPS/RPSS of alpha-smoothed member counts (no\nclimatology blend); distribution of the pooled corrected members against CHIRPS (mean, standard deviation, 10/50/90th\npercentiles, exactly-0 and at-or-below-threshold shares); coverage of the amount and probability scores; how often\neach method's limits, caps and fallbacks act.\nScreening: each method against the reference (operational MVS) per target and score (CRPS, fair CRPS, RPS):\none-sided sign-flip test on the training-design per-year scores and no harm over the test years. Two\nmultiplicity families are reported: within one method across the targets (\"screen_pass\") and across every\ndeclared method and target (\"screen_pass_family\"; sensitivity variants such as the MVS all-zero guard are screened\nwithin method only). A screening pass is not an adoption decision. For the reference comparison, each cell's\ncontribution is also split by its climate group in the fold's training years (all 0 mm, all dry, mixed, always wet).", "gate_rule": "Screening rule (docs/36 rule applied as a screen): a method passes for a target and score if, on the leave-one-year-out 1993-2016 per-year scores, its mean improvement over mvs has a one-sided sign-flip p-value below 0.05 after Holm adjustment, and its mean score over 2017-2025 (fits on 1993-2016) is not worse. 'screen_pass': Holm across the 5 targets of one method. 'screen_pass_family': Holm across every method and target of the benchmark for that score. A screening pass is not an operational adoption decision (see the confirmation run).", "methods": { "raw": { "label": "Raw ECMWF (no correction)", "family": "baseline", "definition": "x' = x (the uncorrected model; baseline, not a candidate)", "references": [ "Johnson et al. 2019" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": {} }, "ls": { "label": "Linear Scaling", "family": "scaling", "definition": "x' = x * mu_obs / mu_model (multiplicative mean correction; ratio 1 where mu_model < 0.1 mm)", "references": [ "Lenderink et al. 2007", "Teutschbein & Seibert 2012" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "min_model_mean": 0.1 } }, "mvs": { "label": "Mean-Variance Scaling (operational)", "family": "scaling", "definition": "x' = max(0, mu_obs + r (x - mu_model)), r = clip(sd_obs/sd_model, 0.5, 2); r = 1 if sd_model < 1 mm", "references": [ "Torralba et al. 2017", "Manzanas et al. 2019" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "ratio_bounds": [ 0.5, 2.0 ], "min_model_sd": 1.0 } }, "vs": { "label": "Variance Scaling (unbounded)", "family": "scaling", "definition": "Same algebra and the same r = 1 fallback (sd_model < 1 mm) as MVS, without the 0.5-2 ratio limits", "references": [ "Teutschbein & Seibert 2012" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "ratio_bounds": null, "min_model_sd": 1.0 } }, "sqrt_mvs": { "label": "Square-root-space Mean-Variance Scaling", "family": "scaling", "definition": "MVS applied to sqrt(x) (r limits 0.5-2; r = 1 if the sqrt-space sd < 0.1), clipped at 0 and squared back (docs/36)", "references": [ "Manzanas et al. 2019" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "ratio_bounds": [ 0.5, 2.0 ], "min_model_sd": 0.1, "space": "sqrt" } }, "pt": { "label": "Power Transformation", "family": "scaling", "definition": "x' = a x^b: b (0.1-3) matches the coefficient of variation where reachable (bound hits reported), a the mean", "references": [ "Leander & Buishand 2007", "Teutschbein & Seibert 2012" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "b_bounds": [ 0.1, 3.0 ] } }, "dc": { "label": "Delta Change", "family": "change-preserving", "definition": "Training-year CHIRPS totals times a = forecast ensemble mean / model mean (a in 0.2-5): historical scenarios, not corrected members", "references": [ "Hay et al. 2000", "Teutschbein & Seibert 2012" ], "member_wise": false, "uses_forecast_distribution": true, "parameters": { "ratio_bounds": [ 0.2, 5.0 ], "min_model_mean": 0.1 } }, "loci": { "label": "Local Intensity Scaling", "family": "scaling", "definition": "Model threshold with the observed frequency of totals above 1 mm, then intensity scaling above it (designed for daily rainfall; here monthly or seasonal totals)", "references": [ "Schmidli et al. 2006" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "wet_threshold": 1.0 } }, "eqm": { "label": "Empirical Quantile Mapping", "family": "quantile mapping", "definition": "x' = Q_obs(F_model(x)) with the dry policy; constant-ratio extrapolation outside the training range", "references": [ "Boe et al. 2007", "Themessl et al. 2011", "Gudmundsson et al. 2012" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "extrapolation": "constant_ratio", "wet_threshold": 1.0 } }, "gqm": { "label": "Gamma Quantile Mapping", "family": "quantile mapping", "definition": "x' = G_obs^-1(G_model(x)), G = dry mass (<= 1 mm) + gamma by weighted maximum likelihood, with the dry policy; linear scaling where fewer than 3 wet values", "references": [ "Piani et al. 2010" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "wet_threshold": 1.0 } }, "dqm": { "label": "Detrended Quantile Mapping", "family": "change-preserving", "definition": "a * EQM(x / a), a = forecast ensemble mean / model mean (0.2-5): removes and reapplies the bounded ratio; exact preservation of the final mean anomaly is not guaranteed", "references": [ "Cannon et al. 2015" ], "member_wise": true, "uses_forecast_distribution": true, "parameters": { "extrapolation": "constant_ratio", "ratio_bounds": [ 0.2, 5.0 ], "min_model_mean": 0.1, "wet_threshold": 1.0 } }, "qdm": { "label": "Quantile Delta Mapping", "family": "change-preserving", "definition": "x' = Q_obs(tau) * x / Q_model(tau), tau = rank of x in the forecast ensemble; change capped at 5 and replaced by Q_obs(tau) where Q_model(tau) <= 1 mm (both reported), so preservation is partial there", "references": [ "Cannon et al. 2015" ], "member_wise": true, "uses_forecast_distribution": true, "parameters": { "max_ratio": 5.0, "wet_threshold": 1.0 } }, "sdm": { "label": "Scaled Distribution Mapping", "family": "change-preserving", "definition": "Switanek et al. (2017) precipitation steps 1-7: gamma fits, recurrence intervals interpolated to the forecast's length, scaled CDF, rain-member count; model climatology with equal-year weights", "references": [ "Switanek et al. 2017" ], "member_wise": true, "uses_forecast_distribution": true, "parameters": { "wet_threshold": 1.0 } }, "cdft": { "label": "CDF-transform", "family": "change-preserving", "definition": "F_obs,f = F_obs(F_model^-1(F_forecast)); x' = F_obs,f^-1(F_forecast(x)); implementation choices: model and forecast first scaled to the CHIRPS mean, values stay within the scaled forecast range", "references": [ "Michelangeli et al. 2009", "Vrac et al. 2012" ], "member_wise": true, "uses_forecast_distribution": true, "parameters": { "min_model_mean": 0.1 } }, "mvs_zero_guard": { "label": "MVS with all-zero guard (variant)", "family": "variant", "definition": "Operational MVS, but corrected totals are 0 mm where every training year has exactly 0 mm (a documented modelling choice, not a physical rule)", "references": [ "Torralba et al. 2017", "Manzanas et al. 2019" ], "member_wise": true, "uses_forecast_distribution": false, "parameters": { "ratio_bounds": [ 0.5, 2.0 ], "min_model_sd": 1.0, "zero_guard": true } } }, "targets": { "Feb": { "tag": "init02_Feb", "cells": 1484, "methods": { "raw": { "training": { "ethiopia": { "years": [ 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016 ], "per_year": { "crps": [ 15.513019816089537, 5.21227288375866, 10.176130399896325, 6.977457975094109, 4.256638449494523, 12.922601020062942, 3.699699249680467, 3.550173134381048, 6.986565668909713, 6.3191901234637475, 12.933746211248174, 6.773763723347948, 4.839161465339081, 12.193191578277185, 8.132875339507383, 4.58818991371913, 7.954151897473313, 25.706245892628367, 5.017858696254736, 3.8021455793911305, 5.402165573392042, 8.479028698973567, 5.3197280413621515, 8.494071953999194 ], "crps_clim": [ 23.284667911212587, 3.570418694039729, 8.664187246161891, 4.414584188793243, 4.17412909889816, 16.25329471183794, 3.8584724401638506, 4.245696599510476, 3.6698911288086773, 3.32770100825122, 7.9273830692352805, 3.158727103335094, 3.386806343170413, 6.902319664533068, 10.632197368513724, 3.1240434276464755, 3.8782525052097263, 28.264469349246895, 2.9648792529408503, 3.872969400259919, 3.1007437566346607, 4.353545654719579, 3.299826968492685, 4.614204893386611 ], "crps_fair": [ 15.19735806638854, 5.141335370554365, 9.971892896672134, 6.835833171655654, 4.213158911113609, 12.535950709322318, 3.5768264572775643, 3.446889798742546, 6.82833079406222, 6.251417911950249, 12.787206547391696, 6.623158287955733, 4.6651898185472715, 11.98125828803723, 7.874041270748008, 4.514174302726384, 7.882091223975455, 25.3650811313416, 4.89415425219712, 3.700962605563519, 5.335209148220749, 8.32505876711236, 5.24215289999863, 8.377594765591455 ], "crps_fair_clim": [ 23.029391203416978, 3.2778043930297773, 8.381220234076412, 4.1235686860688086, 3.882658188806501, 15.98470100934654, 3.5664036954912555, 3.9543612339275516, 3.3774652225615456, 3.0346270146545478, 7.643020594693502, 2.865333083403353, 3.093844291495935, 6.61601578202784, 10.352957648326644, 2.8305837189350216, 3.586221222781536, 28.01862408356878, 2.671118096928818, 3.580928111951141, 2.807239919758411, 4.062414548710915, 3.0067001831540465, 4.323567460178454 ], "rps": [ 0.1936669323198152, 0.314547836194833, 0.5986637293812002, 0.5234595186237833, 0.2962050000629996, 0.33965410929694223, 0.31711994727367193, 0.19159650787177762, 0.7088885590126638, 0.41850205581430794, 0.7845122842781441, 0.6034676439727045, 0.5718354641404123, 0.9580119475784057, 0.44447522035597603, 0.28038959324738577, 0.785621741365326, 0.4074546536811783, 0.5070194085345793, 0.34614175050892004, 0.3552420880570743, 0.8096396636999749, 0.5444975113643564, 0.907975526425214 ], "rps_clim": [ 0.5290059541759002, 0.47988962392562323, 0.4849075877887211, 0.4124150424884049, 0.502955886793367, 0.5029939372693721, 0.45905151377627607, 0.5225990933393452, 0.38206038671438824, 0.4436804395162057, 0.4801714472144227, 0.38090373683663276, 0.4015102412958623, 0.47008446725039066, 0.46611892150198586, 0.47073947275602157, 0.4008721535503825, 0.5160869071930275, 0.3868823232399181, 0.46624256720071, 0.4384388554267233, 0.41402493153199577, 0.41674923105831446, 0.4416090920361355 ], "bias": [ -9.367740649031578, -5.401463926013391, -9.716156721981923, -6.73097521394328, -3.9177195598952337, -5.897745622829028, -2.2219518593743244, -0.7923464245925085, -6.703953063854112, -6.097809018511624, -13.28758677805694, 0.753657984727447, -1.2821379941997277, -10.43832524998765, -4.36362305641719, -4.503763736273779, -8.66599545319972, -17.67594109556689, -3.2655582863386425, -3.090493602016038, -5.509558876270901, -7.540943128658662, -5.451704579495925, -8.877088557238952 ], "mae": [ 20.181598198429963, 5.628846140604801, 12.600400774866268, 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