feat: normales saisonnières 1991-2020 + AnomalyBadge
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- scripts/build-normales.mjs : agrégation TN/TX mensuelles par dept sur la période WMO 1991-2020 depuis les fichiers Q_<DEPT>_previous-1950-2024. Output src/data/normales.json (78 KB, committé). Run annuel max. - Corse : Météo France utilise le code historique "20" (avant split 2A/2B en 1976), donc 2A et 2B partagent la même normale issue de Q_20_*. - src/lib/normales.ts : computeAnomaly() qui moyenne TX/TN des 7 derniers jours, compare à la normale du mois, calcule l'écart en °C et en σ, catégorise (normal / warm / cool / anomaly_warm / anomaly_cool / extreme_warm / extreme_cool / unknown). - src/components/AnomalyBadge.astro : badge coloré (vert/jaune/orange/rouge) visible sur /departement/[code] juste au-dessus du graphe T°. Différencie "il fait chaud" de "il fait anormalement chaud pour ce mois". Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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src/components/AnomalyBadge.astro
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src/components/AnomalyBadge.astro
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---
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import type { Anomaly } from '../lib/normales';
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interface Props {
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anomaly: Anomaly;
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}
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const { anomaly } = Astro.props;
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const CATEGORY_LABEL: Record<Anomaly['txCategory'], { label: string; cls: string; icon: string }> = {
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normal: {
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label: 'Températures dans la normale saisonnière',
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cls: 'border-slate-200 bg-slate-50 text-slate-700',
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icon: '🌡️',
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},
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warm: {
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label: 'Légèrement au-dessus de la normale',
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cls: 'border-yellow-200 bg-yellow-50 text-yellow-900',
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icon: '↗',
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},
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cool: {
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label: 'Légèrement en dessous de la normale',
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cls: 'border-blue-200 bg-blue-50 text-blue-900',
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icon: '↘',
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},
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anomaly_warm: {
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label: 'Anormalement chaud',
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cls: 'border-orange-300 bg-orange-50 text-orange-900',
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icon: '🔥',
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},
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anomaly_cool: {
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label: 'Anormalement frais',
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cls: 'border-blue-300 bg-blue-100 text-blue-900',
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icon: '❄',
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},
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extreme_warm: {
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label: 'Extrêmement chaud (déviation extrême)',
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cls: 'border-red-300 bg-red-50 text-red-900 font-semibold',
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icon: '🚨',
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},
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extreme_cool: {
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label: 'Extrêmement frais (déviation extrême)',
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cls: 'border-blue-400 bg-blue-200 text-blue-900 font-semibold',
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icon: '🚨',
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},
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unknown: {
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label: 'Normale non disponible pour ce mois',
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cls: 'border-slate-200 bg-slate-50 text-slate-500',
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icon: '?',
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},
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};
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const cat = CATEGORY_LABEL[anomaly.txCategory];
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const signDiff = (anomaly.diffTx ?? 0) > 0 ? '+' : '';
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---
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<div class:list={['rounded-lg border p-4', cat.cls]}>
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<div class="flex items-center gap-2 text-sm font-semibold">
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<span aria-hidden="true">{cat.icon}</span>
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<span>{cat.label}</span>
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</div>
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{anomaly.diffTx !== null && anomaly.normaleTx !== null && (
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<p class="mt-2 text-sm">
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<strong>T° max moyenne {anomaly.windowDays} derniers jours :</strong>{' '}
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<span class="font-mono">{anomaly.meanTx}°C</span>
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<span class="text-slate-500"> · normale du mois (1991-2020) : <span class="font-mono">{anomaly.normaleTx}°C</span></span>
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</p>
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<p class="mt-1 text-sm">
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<strong>Écart :</strong>{' '}
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<span class="font-mono">{signDiff}{anomaly.diffTx}°C</span>
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{anomaly.sigmaTx !== null && (
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<span class="text-xs text-slate-500"> ({anomaly.sigmaTx > 0 ? '+' : ''}{anomaly.sigmaTx}σ)</span>
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)}
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</p>
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)}
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<p class="mt-2 text-xs text-slate-500">
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Comparaison sur la période de référence WMO 1991-2020. σ = écart-type, mesure de l'amplitude
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historique du mois ; au-delà de 2σ l'événement est statistiquement rare.
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</p>
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</div>
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1
src/data/normales.json
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src/data/normales.json
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src/lib/normales.ts
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src/lib/normales.ts
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// Lookup des normales saisonnières TN/TX par dept × mois, calculées sur 1991-2020.
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// Données générées par scripts/build-normales.mjs, committées en JSON statique.
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import type { DayObservation } from './climato';
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let normalesData: Record<string, MonthNormale[] | null> | null = null;
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async function loadNormales(): Promise<Record<string, MonthNormale[] | null>> {
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if (normalesData) return normalesData;
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try {
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const m = await import('../data/normales.json');
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normalesData = m.default as Record<string, MonthNormale[] | null>;
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} catch {
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normalesData = {};
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}
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return normalesData;
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}
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export interface MonthNormale {
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month: number; // 1..12
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tn: number | null;
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tx: number | null;
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tnStd: number;
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txStd: number;
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n: number;
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}
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export async function normaleForMonth(dept: string, month: number): Promise<MonthNormale | null> {
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const data = await loadNormales();
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const arr = data[dept];
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if (!arr) return null;
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return arr[month - 1] ?? null;
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}
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export interface Anomaly {
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windowDays: number;
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meanTx: number | null;
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meanTn: number | null;
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normaleTx: number | null;
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normaleTn: number | null;
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diffTx: number | null;
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diffTn: number | null;
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sigmaTx: number | null; // diffTx / txStd
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sigmaTn: number | null;
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/**
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* - 'normal' : |sigma| <= 1
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* - 'warm' / 'cool' : 1 < |sigma| <= 2
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* - 'anomaly_warm' / 'anomaly_cool' : |sigma| > 2 (déviation significative)
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* - 'extreme_warm' / 'extreme_cool' : |sigma| > 3
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* - 'unknown' : pas de normale
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*/
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txCategory: 'normal' | 'warm' | 'cool' | 'anomaly_warm' | 'anomaly_cool' | 'extreme_warm' | 'extreme_cool' | 'unknown';
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}
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function categorize(sigma: number | null): Anomaly['txCategory'] {
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if (sigma === null || !Number.isFinite(sigma)) return 'unknown';
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const abs = Math.abs(sigma);
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if (abs > 3) return sigma > 0 ? 'extreme_warm' : 'extreme_cool';
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if (abs > 2) return sigma > 0 ? 'anomaly_warm' : 'anomaly_cool';
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if (abs > 1) return sigma > 0 ? 'warm' : 'cool';
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return 'normal';
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}
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export async function computeAnomaly(dept: string, days: DayObservation[]): Promise<Anomaly | null> {
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if (days.length === 0) return null;
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const recent = days.slice(-7);
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if (recent.length === 0) return null;
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// Représentatif : moyenne des 7 derniers jours
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const txs = recent.map((d) => d.tx).filter((v): v is number => v !== null);
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const tns = recent.map((d) => d.tn).filter((v): v is number => v !== null);
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const meanTx = txs.length ? +(txs.reduce((s, v) => s + v, 0) / txs.length).toFixed(1) : null;
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const meanTn = tns.length ? +(tns.reduce((s, v) => s + v, 0) / tns.length).toFixed(1) : null;
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// Mois représentatif : médian des 7 jours
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const middleDate = recent[Math.floor(recent.length / 2)].date;
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const month = parseInt(middleDate.slice(5, 7), 10);
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const nrm = await normaleForMonth(dept, month);
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if (!nrm) return null;
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const diffTx = meanTx !== null && nrm.tx !== null ? +(meanTx - nrm.tx).toFixed(1) : null;
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const diffTn = meanTn !== null && nrm.tn !== null ? +(meanTn - nrm.tn).toFixed(1) : null;
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const sigmaTx = diffTx !== null && nrm.txStd > 0 ? +(diffTx / nrm.txStd).toFixed(2) : null;
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const sigmaTn = diffTn !== null && nrm.tnStd > 0 ? +(diffTn / nrm.tnStd).toFixed(2) : null;
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return {
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windowDays: recent.length,
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meanTx,
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meanTn,
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normaleTx: nrm.tx,
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normaleTn: nrm.tn,
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diffTx,
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diffTn,
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sigmaTx,
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sigmaTn,
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txCategory: categorize(sigmaTx),
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};
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}
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@ -7,7 +7,9 @@ import { getDepartement, isDrom } from '../../lib/departements';
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import { PHENOMENA, COLOR_LABEL } from '../../lib/phenomena';
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import { ADVICE, EMERGENCY_NUMBERS } from '../../lib/advice';
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import { getClimatoForDepartement } from '../../lib/climato';
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import { computeAnomaly } from '../../lib/normales';
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import ClimatoChart from '../../components/ClimatoChart.astro';
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import AnomalyBadge from '../../components/AnomalyBadge.astro';
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export const prerender = false;
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@ -31,9 +33,13 @@ if (!drom) {
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}
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let climato = null;
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let anomaly = null;
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if (!drom) {
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try {
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climato = await getClimatoForDepartement(dept.code);
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if (climato?.days?.length) {
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anomaly = await computeAnomaly(dept.code, climato.days);
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}
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} catch (e) {
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console.warn('climato fetch failed for', dept.code, (e as Error).message);
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}
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@ -147,10 +153,16 @@ const adviceFor = highest && ADVICE[highest.phenomenonId];
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<section class="border-t border-slate-200 bg-slate-50">
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<div class="container-tight py-8">
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<h2 class="mb-4 text-xl font-semibold">Températures récentes</h2>
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{anomaly && (
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<div class="mb-4">
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<AnomalyBadge anomaly={anomaly} />
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</div>
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)}
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<ClimatoChart days={climato.days} />
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<p class="mt-2 text-xs text-slate-500">
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Source : Météo France — données climatologiques de base quotidiennes, agrégées par moyenne
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sur toutes les stations du département. Donnée brute, contrôle qualité Météo France.
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Normales calculées sur 1991-2020 (référence WMO).
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</p>
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</div>
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</section>
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