AmandaloveYang
2325 lines
84 KiB
TypeScript
2325 lines
84 KiB
TypeScript
import { Locale } from "@/lib/i18n";
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import {
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AiAnalysisStructured,
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CityDetail,
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HistoryPoint,
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NearbyStation,
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} from "@/lib/dashboard-types";
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import {
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getNoaaStationCode,
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getNoaaStationName,
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getObservationSourceCode,
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getObservationSourceTag,
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getRealtimeObservationTag,
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isTurkishMgmCity,
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} from "@/lib/observation-source-utils";
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import {
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formatTemperatureValue,
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normalizeTemperatureLabel,
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normalizeTemperatureSymbol,
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} from "@/lib/temperature-utils";
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import { formatTafMarkerType } from "@/lib/taf-utils";
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import { normalizeHm } from "@/lib/time-utils";
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import { getWeatherSummary } from "@/lib/weather-summary-utils";
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export { getTemperatureChartData } from "@/lib/chart-utils";
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export { getModelView, getProbabilityView } from "@/lib/model-utils";
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export { getTodayPaceView } from "@/lib/pace-utils";
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export {
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getHeroMetaItems,
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getRiskBadgeLabel,
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getWeatherSummary,
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translateMetar,
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} from "@/lib/weather-summary-utils";
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export {
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formatTemperatureValue,
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normalizeTemperatureLabel,
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normalizeTemperatureSymbol,
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} from "@/lib/temperature-utils";
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function isEnglish(locale: Locale) {
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return locale === "en-US";
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}
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function containsCjk(text: string) {
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return /[\u3400-\u9fff]/.test(text);
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}
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function getLocalizedDynamicCommentary(
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detail: CityDetail,
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locale: Locale,
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): { headline: string; bullets: string[]; source: string } {
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const commentary = detail.dynamic_commentary || {};
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const preferEnglish = isEnglish(locale);
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const rawHeadline = preferEnglish
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? String(commentary.headline_en || "").trim()
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: String(commentary.headline_zh || "").trim();
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const rawBullets = preferEnglish
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? commentary.bullets_en
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: commentary.bullets_zh;
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const bullets = Array.isArray(rawBullets)
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? rawBullets.map((item) => String(item || "").trim()).filter(Boolean)
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: [];
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const fallbackHeadline = String(commentary.summary || "").trim();
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const fallbackBullets = Array.isArray(commentary.notes)
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? commentary.notes.map((item) => String(item || "").trim()).filter(Boolean)
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: [];
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return {
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headline: rawHeadline || fallbackHeadline,
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bullets: bullets.length > 0 ? bullets : fallbackBullets,
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source: String(commentary.source || "").trim(),
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};
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}
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export function parseAiAnalysis(analysis: CityDetail["ai_analysis"]) {
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const fallback = {
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bullets: [] as string[],
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summary: "",
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};
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if (!analysis) return fallback;
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if (typeof analysis === "string") {
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return {
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bullets: [],
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summary: analysis.trim(),
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};
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}
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const structured = analysis as AiAnalysisStructured;
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return {
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bullets: Array.isArray(structured.highlights)
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? structured.highlights
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: Array.isArray(structured.points)
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? structured.points
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: [],
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summary: structured.summary || structured.text || structured.message || "",
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};
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}
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export function getAirportNarrative(
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detail: CityDetail,
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locale: Locale = "zh-CN",
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) {
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const parsed = parseAiAnalysis(detail.ai_analysis);
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if (!isEnglish(locale)) return parsed;
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const englishSummary = containsCjk(parsed.summary) ? "" : parsed.summary.trim();
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const englishBullets = parsed.bullets
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.map((item) => String(item || "").trim())
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.filter((item) => item && !containsCjk(item));
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if (englishSummary || englishBullets.length > 0) {
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return {
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bullets: englishBullets,
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summary: englishSummary,
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};
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}
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const sourceLabel =
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String(detail.current?.settlement_source_label || "").trim() ||
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String(detail.risk?.icao || "").trim() ||
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String(detail.risk?.airport || "").trim() ||
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String(detail.display_name || detail.name || "").trim() ||
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"Airport";
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const currentTemp = Number(detail.current?.temp);
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const tempText = Number.isFinite(currentTemp)
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? `${currentTemp}${detail.temp_symbol || "°C"}`
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: null;
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const obsTime = String(detail.current?.obs_time || "").trim();
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const weatherText = getWeatherSummary(detail, locale).weatherText.toLowerCase();
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const windBucket = bucketLabel(
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trendBucketFromDir(detail.current?.wind_dir ?? null),
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locale,
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);
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const windSpeedKt = Number(detail.current?.wind_speed_kt);
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const tafSummary = String(detail.taf?.signal?.summary_en || "").trim();
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const windPhrase = Number.isFinite(windSpeedKt)
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? `${windBucket} around ${windSpeedKt} kt`
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: `${windBucket} prevailing`;
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const summaryParts = [
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tempText
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? `${sourceLabel} reports ${tempText}${obsTime ? ` at ${obsTime}` : ""}, ${weatherText}.`
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: `${sourceLabel} reports ${weatherText}${obsTime ? ` at ${obsTime}` : ""}.`,
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`${windPhrase}.`,
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tafSummary,
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].filter(Boolean);
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const bullets: string[] = [];
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const rawMetar = String(detail.current?.raw_metar || "").trim();
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if (rawMetar) {
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bullets.push(`Latest METAR: ${rawMetar}`);
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}
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if (tafSummary) {
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bullets.push(`TAF signal: ${tafSummary}`);
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}
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if (detail.taf?.raw_taf) {
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bullets.push(`TAF available for airport-side timing checks.`);
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}
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return {
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bullets,
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summary: summaryParts.join(" "),
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};
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}
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export function pickAnkaraNearbyStations(stations: NearbyStation[]) {
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const preferredNames = [
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"Airport (MGM/17128)",
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"Ankara (Bölge/Center)",
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"Ankara (Bolge/Center)",
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"Etimesgut",
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"Pursaklar",
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"Cubuk",
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"Çubuk",
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"Kalecik",
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];
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const picks = preferredNames
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.map((name) => stations.find((station) => station?.name === name))
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.filter(Boolean) as NearbyStation[];
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return picks.length ? picks : stations;
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}
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function distanceKm(
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lat1: number,
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lon1: number,
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lat2: number,
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lon2: number,
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) {
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const toRad = (deg: number) => (deg * Math.PI) / 180;
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const dLat = toRad(lat2 - lat1);
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const dLon = toRad(lon2 - lon1);
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const a =
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Math.sin(dLat / 2) ** 2 +
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Math.cos(toRad(lat1)) *
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Math.cos(toRad(lat2)) *
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Math.sin(dLon / 2) ** 2;
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return 6371 * 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a));
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}
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export function pickMapNearbyStations(detail: CityDetail) {
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const stations = Array.isArray(detail.official_nearby)
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? detail.official_nearby
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: Array.isArray(detail.mgm_nearby)
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? detail.mgm_nearby
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: [];
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const city = String(detail.name || detail.display_name || "")
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.trim()
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.toLowerCase();
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if (city === "seoul" || city === "busan") {
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return [];
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}
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if (city === "ankara") {
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return pickAnkaraNearbyStations(stations);
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}
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if (city === "istanbul" && Number.isFinite(detail.lat) && Number.isFinite(detail.lon)) {
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const preferredTokens = [
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"havalimani",
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"havalimanı",
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"arnavutkoy",
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"arnavutköy",
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"liman feneri",
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];
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const scored = stations
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.map((station) => {
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const lat = Number(station.lat);
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const lon = Number(station.lon);
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if (!Number.isFinite(lat) || !Number.isFinite(lon)) {
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return null;
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}
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const name = String(station.name || "").toLowerCase();
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const preferred = preferredTokens.some((token) => name.includes(token));
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return {
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preferred,
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station,
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km: distanceKm(Number(detail.lat), Number(detail.lon), lat, lon),
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};
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})
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.filter(Boolean) as Array<{
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preferred: boolean;
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station: NearbyStation;
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km: number;
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}>;
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const closePreferred = scored
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.filter((row) => row.preferred && row.km <= 18)
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.sort((a, b) => a.km - b.km)
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.map((row) => row.station);
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const closeFallback = scored
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.filter((row) => row.km <= 8)
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.sort((a, b) => a.km - b.km)
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.map((row) => row.station);
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const merged = [...closePreferred, ...closeFallback].filter(
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(station, index, list) =>
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list.findIndex(
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(row) =>
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row.name === station.name &&
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row.lat === station.lat &&
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row.lon === station.lon,
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) === index,
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);
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return merged.slice(0, 3);
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}
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return stations;
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}
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export function getFutureSlice(detail: CityDetail, dateStr: string) {
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const hourly = detail.hourly_next_48h || {};
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const times = hourly.times || [];
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const slice: Array<{
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cloudCover: number | null;
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dewPoint: number | null;
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label: string;
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precipProb: number | null;
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pressure: number | null;
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radiation: number | null;
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temp: number | null;
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time: string;
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windDir: number | null;
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windSpeed: number | null;
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}> = [];
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for (let index = 0; index < times.length; index += 1) {
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const timestamp = times[index];
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if (!timestamp || !String(timestamp).startsWith(dateStr)) continue;
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slice.push({
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cloudCover: hourly.cloud_cover?.[index] ?? null,
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dewPoint: hourly.dew_point?.[index] ?? null,
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label: String(timestamp).split("T")[1]?.slice(0, 5) || timestamp,
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precipProb: hourly.precipitation_probability?.[index] ?? null,
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pressure: hourly.pressure_msl?.[index] ?? null,
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radiation: hourly.radiation?.[index] ?? null,
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temp: hourly.temps?.[index] ?? null,
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time: timestamp,
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windDir: hourly.wind_direction_10m?.[index] ?? null,
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windSpeed: hourly.wind_speed_10m?.[index] ?? null,
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});
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}
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return slice;
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}
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function trendBucketFromDir(direction?: number | null) {
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const value = Number(direction);
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if (!Number.isFinite(value)) return null;
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if (value >= 135 && value <= 240) return "southerly";
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if (value >= 290 || value <= 45) return "northerly";
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if (value > 45 && value < 135) return "easterly";
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return "westerly";
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}
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function bucketLabel(bucket: string | null, locale: Locale = "zh-CN") {
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if (isEnglish(locale)) {
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return (
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{
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southerly: "S / SW wind",
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northerly: "N / NW wind",
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easterly: "E wind",
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westerly: "W wind",
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}[bucket || ""] || "Unknown wind direction"
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);
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}
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return (
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{
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southerly: "南 / 西南风",
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northerly: "北 / 西北风",
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easterly: "东风",
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westerly: "西风",
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}[bucket || ""] || "风向不明"
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);
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}
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export function wuRound(value: number | null | undefined) {
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const numeric = Number(value);
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if (!Number.isFinite(numeric)) return null;
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return numeric >= 0
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? Math.floor(numeric + 0.5)
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: Math.ceil(numeric - 0.5);
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}
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export function formatDelta(value: number | null | undefined, suffix = "") {
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const numeric = Number(value);
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if (!Number.isFinite(numeric)) return "--";
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const sign = numeric > 0 ? "+" : "";
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return `${sign}${numeric.toFixed(1)}${suffix}`;
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}
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function getForecastTextForDate(detail: CityDetail, dateStr: string) {
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const periods = detail.source_forecasts?.weather_gov?.forecast_periods || [];
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return periods.filter((period) =>
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String(period.start_time || "").startsWith(dateStr),
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);
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}
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export function computeFrontTrendSignal(
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detail: CityDetail,
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dateStr: string,
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locale: Locale = "zh-CN",
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) {
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const upperAirSignal = detail.vertical_profile_signal || {};
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const tafSignal = detail.taf?.signal || {};
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const upperAirTradeCue = upperAirSignal.source
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? upperAirSignal.heating_setup === "supportive"
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? {
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label: isEnglish(locale) ? "Trade cue" : "交易动作",
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note: isEnglish(locale)
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? "The setup still supports further warming. Do not call the high too early."
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: "结构仍支持继续升温，别太早押高温见顶。",
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tone: "warm",
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value: isEnglish(locale) ? "Lean warmer" : "偏暖侧",
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}
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: upperAirSignal.heating_setup === "suppressed"
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? {
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label: isEnglish(locale) ? "Trade cue" : "交易动作",
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note: isEnglish(locale)
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? "Further upside looks less reliable. Do not chase the high blindly."
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: "高温继续上冲的把握不大，别盲目追热。",
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tone: "cold",
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value: isEnglish(locale) ? "Lean cautious" : "偏谨慎",
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}
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: {
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label: isEnglish(locale) ? "Trade cue" : "交易动作",
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note: isEnglish(locale)
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? "The picture is still mixed. Let the next move decide first."
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: "现在还看不出明确方向，先等下一步走势确认。",
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tone: "",
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value: isEnglish(locale) ? "Wait / confirm" : "先观察",
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}
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: null;
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const baseUpperAirSummary = upperAirSignal.source
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? (() => {
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const hasMetrics =
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upperAirSignal.cape_max != null ||
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upperAirSignal.cin_min != null ||
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upperAirSignal.boundary_layer_height_max != null ||
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upperAirSignal.shear_10m_180m_max != null;
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if (!hasMetrics) {
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return isEnglish(locale)
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? "Upper-air inputs are incomplete. For now, trade direction should rely more on surface structure."
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: "高空输入还不完整，当前交易方向先更多参考近地面结构信号。";
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}
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if (upperAirSignal.heating_setup === "supportive") {
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return isEnglish(locale)
|
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? "Upper-air structure still favors further warming. Do not call the high too early."
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: "高空结构仍偏向继续增温，别太早押高温见顶。";
|
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}
|
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if (upperAirSignal.heating_setup === "suppressed") {
|
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return isEnglish(locale)
|
||
? "Upper-air structure leans toward capping the afternoon high. Further upside looks less reliable."
|
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: "高空结构更偏向压住午后峰值，高温继续上冲的把握不大。";
|
||
}
|
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return isEnglish(locale)
|
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? "Upper-air structure is fairly neutral. It does not provide a clean edge yet."
|
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: "高空结构整体偏中性，暂时还给不出明确方向。";
|
||
})()
|
||
: "";
|
||
const tafSummary =
|
||
tafSignal.available && dateStr === detail.local_date
|
||
? isEnglish(locale)
|
||
? String(tafSignal.summary_en || "").trim()
|
||
: String(tafSignal.summary_zh || "").trim()
|
||
: "";
|
||
let upperAirSummary = baseUpperAirSummary;
|
||
let tafMetric:
|
||
| {
|
||
label: string;
|
||
note: string;
|
||
tone?: string;
|
||
value: string;
|
||
}
|
||
| null = null;
|
||
let upperAirMetrics: Array<{
|
||
label: string;
|
||
note: string;
|
||
tone?: string;
|
||
value: string;
|
||
}> = [];
|
||
const localizedCommentary =
|
||
dateStr === detail.local_date
|
||
? getLocalizedDynamicCommentary(detail, locale)
|
||
: { headline: "", bullets: [], source: "" };
|
||
const backendSummary =
|
||
localizedCommentary.headline &&
|
||
(!isEnglish(locale) || !containsCjk(localizedCommentary.headline))
|
||
? localizedCommentary.headline
|
||
: "";
|
||
const backendNotes = localizedCommentary.bullets.filter(
|
||
(note) => !isEnglish(locale) || !containsCjk(note),
|
||
);
|
||
const slice = getFutureSlice(detail, dateStr);
|
||
const currentTemp = Number(detail.current?.temp);
|
||
const currentDew = Number(detail.current?.dewpoint);
|
||
|
||
if (!slice.length) {
|
||
const fallbackSummary =
|
||
backendSummary ||
|
||
(isEnglish(locale)
|
||
? "Insufficient intraday structured data. Keep baseline monitoring."
|
||
: "当日日内结构化数据不足，暂时只保留基础监控。");
|
||
return {
|
||
confidence: "low",
|
||
label: isEnglish(locale) ? "Monitoring" : "监控中",
|
||
metrics: [] as Array<{
|
||
label: string;
|
||
note: string;
|
||
tone?: string;
|
||
value: string;
|
||
}>,
|
||
upperAirMetrics,
|
||
upperAirSummary,
|
||
precipMax: 0,
|
||
score: 0,
|
||
summary: fallbackSummary,
|
||
summaryLines: [fallbackSummary],
|
||
weatherGovPeriods: [] as ReturnType<typeof getForecastTextForDate>,
|
||
};
|
||
}
|
||
|
||
const normalizeHm = (value: unknown): string | null => {
|
||
const match = String(value || "").match(/(\d{1,2}):(\d{2})/);
|
||
if (!match) return null;
|
||
const hour = Number.parseInt(match[1], 10);
|
||
const minute = Number.parseInt(match[2], 10);
|
||
if (
|
||
!Number.isFinite(hour) ||
|
||
!Number.isFinite(minute) ||
|
||
hour < 0 ||
|
||
hour > 23 ||
|
||
minute < 0 ||
|
||
minute > 59
|
||
) {
|
||
return null;
|
||
}
|
||
return `${String(hour).padStart(2, "0")}:${String(minute).padStart(2, "0")}`;
|
||
};
|
||
const hmToMinutes = (value: string | null) => {
|
||
if (!value) return null;
|
||
const [hourPart, minutePart] = value.split(":");
|
||
const hour = Number.parseInt(hourPart || "", 10);
|
||
const minute = Number.parseInt(minutePart || "", 10);
|
||
if (
|
||
!Number.isFinite(hour) ||
|
||
!Number.isFinite(minute) ||
|
||
hour < 0 ||
|
||
hour > 23 ||
|
||
minute < 0 ||
|
||
minute > 59
|
||
) {
|
||
return null;
|
||
}
|
||
return hour * 60 + minute;
|
||
};
|
||
const pointMinutes = (point: { label?: string }) =>
|
||
hmToMinutes(normalizeHm(point.label));
|
||
|
||
const isTargetToday = dateStr === detail.local_date;
|
||
const currentHm = normalizeHm(detail.local_time);
|
||
const sunsetHm = normalizeHm(detail.forecast?.sunset);
|
||
const peakFirstHour = Number(detail.peak?.first_h);
|
||
const peakLastHour = Number(detail.peak?.last_h);
|
||
const hasPeakWindow =
|
||
Number.isFinite(peakFirstHour) &&
|
||
Number.isFinite(peakLastHour) &&
|
||
peakFirstHour >= 0 &&
|
||
peakLastHour >= peakFirstHour;
|
||
const currentMinutes = hmToMinutes(currentHm);
|
||
const sunsetMinutes = hmToMinutes(sunsetHm);
|
||
const peakWindowStartMinutes = hasPeakWindow
|
||
? Math.max(0, (peakFirstHour - 2) * 60)
|
||
: null;
|
||
const peakWindowEndMinutes = hasPeakWindow
|
||
? Math.min(23 * 60 + 59, (peakLastHour + 1) * 60)
|
||
: null;
|
||
const canUseSunsetWindow =
|
||
isTargetToday &&
|
||
currentMinutes !== null &&
|
||
sunsetMinutes !== null &&
|
||
sunsetMinutes > currentMinutes;
|
||
const tafMarkers = Array.isArray(tafSignal.markers) ? tafSignal.markers : [];
|
||
const markerSummary = (
|
||
marker:
|
||
| {
|
||
marker_type?: string | null;
|
||
start_local?: string | null;
|
||
end_local?: string | null;
|
||
suppression_level?: string | null;
|
||
summary_zh?: string | null;
|
||
summary_en?: string | null;
|
||
}
|
||
| null
|
||
| undefined,
|
||
) =>
|
||
!marker
|
||
? ""
|
||
: isEnglish(locale)
|
||
? String(marker.summary_en || "").trim()
|
||
: String(marker.summary_zh || "").trim();
|
||
const currentTafMarker =
|
||
tafSignal.available && currentMinutes !== null
|
||
? tafMarkers.find((marker) => {
|
||
const start = hmToMinutes(normalizeHm(marker?.start_local));
|
||
const end = hmToMinutes(normalizeHm(marker?.end_local));
|
||
if (start === null || end === null) return false;
|
||
return currentMinutes >= start && currentMinutes <= end;
|
||
})
|
||
: null;
|
||
const nextTafMarker =
|
||
tafSignal.available && currentMinutes !== null && !currentTafMarker
|
||
? tafMarkers.find((marker) => {
|
||
const start = hmToMinutes(normalizeHm(marker?.start_local));
|
||
return start !== null && start > currentMinutes;
|
||
})
|
||
: null;
|
||
const sameMarker = (
|
||
left:
|
||
| { marker_type?: string | null; start_local?: string | null; end_local?: string | null }
|
||
| null
|
||
| undefined,
|
||
right:
|
||
| { marker_type?: string | null; start_local?: string | null; end_local?: string | null }
|
||
| null
|
||
| undefined,
|
||
) =>
|
||
!!left &&
|
||
!!right &&
|
||
String(left.marker_type || "") === String(right.marker_type || "") &&
|
||
String(left.start_local || "") === String(right.start_local || "") &&
|
||
String(left.end_local || "") === String(right.end_local || "");
|
||
const formatTafSegmentBody = (
|
||
marker:
|
||
| {
|
||
marker_type?: string | null;
|
||
start_local?: string | null;
|
||
end_local?: string | null;
|
||
suppression_level?: string | null;
|
||
}
|
||
| null
|
||
| undefined,
|
||
kind: "current" | "next" | "peak",
|
||
) => {
|
||
if (!marker) return "";
|
||
const range = `${normalizeHm(marker.start_local) || "--:--"}-${normalizeHm(marker.end_local) || "--:--"}`;
|
||
const typeLabel = formatTafMarkerType(
|
||
String(marker.marker_type || ""),
|
||
locale,
|
||
);
|
||
const level = String(marker.suppression_level || "low").toLowerCase();
|
||
const statusText = isEnglish(locale)
|
||
? level === "high"
|
||
? "shows shower or thunderstorm disruption"
|
||
: level === "medium"
|
||
? "shows cloud or light-rain disruption"
|
||
: "stays relatively stable"
|
||
: level === "high"
|
||
? "有阵雨或雷暴扰动"
|
||
: level === "medium"
|
||
? "有云量或弱降水扰动"
|
||
: "以稳定为主";
|
||
return isEnglish(locale)
|
||
? `${typeLabel} (${range}), ${statusText}.`
|
||
: `${typeLabel}（${range}），${statusText}。`;
|
||
};
|
||
const peakWindowTafMarker =
|
||
tafSignal.available &&
|
||
peakWindowStartMinutes !== null &&
|
||
peakWindowEndMinutes !== null
|
||
? tafMarkers.find((marker) => {
|
||
const start = hmToMinutes(normalizeHm(marker?.start_local));
|
||
const end = hmToMinutes(normalizeHm(marker?.end_local));
|
||
if (start === null || end === null) return false;
|
||
return start <= peakWindowEndMinutes && end >= peakWindowStartMinutes;
|
||
})
|
||
: null;
|
||
const peakTafSummary = markerSummary(peakWindowTafMarker);
|
||
const peakTafStillRelevant =
|
||
peakWindowEndMinutes === null ||
|
||
currentMinutes === null ||
|
||
currentMinutes < peakWindowEndMinutes;
|
||
const effectivePeakTafSummary =
|
||
peakTafStillRelevant &&
|
||
peakTafSummary &&
|
||
!sameMarker(peakWindowTafMarker, currentTafMarker) &&
|
||
!sameMarker(peakWindowTafMarker, nextTafMarker)
|
||
? peakTafSummary
|
||
: "";
|
||
const currentTafLine = currentTafMarker
|
||
? isEnglish(locale)
|
||
? `Use current TAF as primary: ${formatTafSegmentBody(currentTafMarker, "current")}`
|
||
: `以当前 TAF 为准：${formatTafSegmentBody(currentTafMarker, "current")}`
|
||
: nextTafMarker
|
||
? isEnglish(locale)
|
||
? `Use next TAF segment as primary: ${formatTafSegmentBody(nextTafMarker, "next")}`
|
||
: `以下一段 TAF 为准：${formatTafSegmentBody(nextTafMarker, "next")}`
|
||
: "";
|
||
const currentTafLineForSummary = currentTafLine.replace(/^Use (current|next) TAF (as primary|segment as primary):\s*/i, "").replace(/^以(当前|下一段) TAF 为准：/, "");
|
||
const peakTafLine =
|
||
effectivePeakTafSummary && peakWindowTafMarker
|
||
? isEnglish(locale)
|
||
? `Peak-window reference: ${formatTafSegmentBody(peakWindowTafMarker, "peak")}`
|
||
: `峰值窗口参考：${formatTafSegmentBody(peakWindowTafMarker, "peak")}`
|
||
: "";
|
||
const peakTafLineForSummary = peakTafLine.replace(/^Peak-window reference:\s*/i, "").replace(/^峰值窗口参考：/, "");
|
||
const tafFallbackSummary =
|
||
currentTafLine || peakTafLine ? "" : tafSummary;
|
||
const tafPrimarySummary = currentTafMarker
|
||
? isEnglish(locale)
|
||
? `Use current TAF as primary: ${currentTafLineForSummary}`
|
||
: `以当前 TAF 为准：${currentTafLineForSummary}`
|
||
: nextTafMarker
|
||
? isEnglish(locale)
|
||
? `Use next TAF segment as primary: ${currentTafLineForSummary}`
|
||
: `以下一段 TAF 为准：${currentTafLineForSummary}`
|
||
: "";
|
||
const tafReferenceSummary =
|
||
peakTafLineForSummary &&
|
||
peakTafLineForSummary !== currentTafLineForSummary
|
||
? isEnglish(locale)
|
||
? `Peak-window reference: ${peakTafLineForSummary}`
|
||
: `峰值窗口参考：${peakTafLineForSummary}`
|
||
: "";
|
||
upperAirSummary = [
|
||
baseUpperAirSummary,
|
||
tafPrimarySummary,
|
||
tafReferenceSummary,
|
||
tafFallbackSummary,
|
||
]
|
||
.filter(Boolean)
|
||
.join(isEnglish(locale) ? " " : "");
|
||
tafMetric =
|
||
tafSignal.available && dateStr === detail.local_date
|
||
? {
|
||
label: isEnglish(locale) ? "Airport TAF" : "机场预报",
|
||
note:
|
||
tafPrimarySummary ||
|
||
tafReferenceSummary ||
|
||
tafFallbackSummary ||
|
||
(isEnglish(locale)
|
||
? "Airport TAF is available for the current peak window."
|
||
: "当前峰值窗口已接入机场 TAF 预报。"),
|
||
tone:
|
||
tafSignal.suppression_level === "high"
|
||
? "cold"
|
||
: tafSignal.suppression_level === "low"
|
||
? "warm"
|
||
: "",
|
||
value:
|
||
tafSignal.suppression_level === "high"
|
||
? isEnglish(locale)
|
||
? "Suppression watch"
|
||
: "防压温"
|
||
: tafSignal.suppression_level === "medium"
|
||
? isEnglish(locale)
|
||
? "Watch clouds/rain"
|
||
: "看云雨"
|
||
: isEnglish(locale)
|
||
? "Mostly stable"
|
||
: "暂稳",
|
||
}
|
||
: null;
|
||
upperAirMetrics = upperAirSignal.source
|
||
? [
|
||
...(upperAirTradeCue ? [upperAirTradeCue] : []),
|
||
{
|
||
label: isEnglish(locale) ? "Peak setup" : "冲高环境",
|
||
note:
|
||
upperAirSignal.heating_setup === "supportive"
|
||
? isEnglish(locale)
|
||
? "Still supportive of more daytime heating. Do not call the high too early."
|
||
: "结构仍支持白天继续升温，别太早押高温见顶。"
|
||
: upperAirSignal.heating_setup === "suppressed"
|
||
? isEnglish(locale)
|
||
? "Leans toward capping the afternoon peak. Further upside looks less reliable."
|
||
: "更偏向压住午后峰值，高温继续上冲的把握不大。"
|
||
: isEnglish(locale)
|
||
? "Neutral on its own. It does not provide a clear directional edge yet."
|
||
: "单看这层偏中性，暂时还没有明确方向优势。",
|
||
tone:
|
||
upperAirSignal.heating_setup === "supportive"
|
||
? "warm"
|
||
: upperAirSignal.heating_setup === "suppressed"
|
||
? "cold"
|
||
: "",
|
||
value:
|
||
upperAirSignal.heating_setup === "supportive"
|
||
? isEnglish(locale)
|
||
? "Supportive"
|
||
: "偏支持"
|
||
: upperAirSignal.heating_setup === "suppressed"
|
||
? isEnglish(locale)
|
||
? "Suppressed"
|
||
: "偏压制"
|
||
: isEnglish(locale)
|
||
? "Neutral"
|
||
: "中性",
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Peak suppression risk" : "压温风险",
|
||
note:
|
||
upperAirSignal.cape_max != null || upperAirSignal.cin_min != null
|
||
? isEnglish(locale)
|
||
? `How likely clouds or showers are to cap the high. CAPE ${Math.round(Number(upperAirSignal.cape_max ?? 0))}, CIN ${Number(upperAirSignal.cin_min ?? 0).toFixed(0)}.`
|
||
: `看云和阵雨有多大概率把峰值压住。CAPE ${Math.round(Number(upperAirSignal.cape_max ?? 0))}，CIN ${Number(upperAirSignal.cin_min ?? 0).toFixed(0)}。`
|
||
: isEnglish(locale)
|
||
? "Estimated from the next 48h upper-air profile."
|
||
: "根据未来 48 小时高空剖面估算。",
|
||
tone:
|
||
upperAirSignal.suppression_risk === "high"
|
||
? "cold"
|
||
: upperAirSignal.suppression_risk === "low"
|
||
? "warm"
|
||
: "",
|
||
value:
|
||
upperAirSignal.suppression_risk === "high"
|
||
? isEnglish(locale)
|
||
? "High"
|
||
: "高"
|
||
: upperAirSignal.suppression_risk === "medium"
|
||
? isEnglish(locale)
|
||
? "Medium"
|
||
: "中"
|
||
: isEnglish(locale)
|
||
? "Low"
|
||
: "低",
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Afternoon disruption" : "午后扰动",
|
||
note:
|
||
upperAirSignal.lifted_index_min != null
|
||
? isEnglish(locale)
|
||
? `How easily the afternoon can turn noisy. Lifted Index ${Number(upperAirSignal.lifted_index_min).toFixed(1)}.`
|
||
: `看午后是否容易突然起云、起对流，把走势搅乱。Lifted Index ${Number(upperAirSignal.lifted_index_min).toFixed(1)}。`
|
||
: isEnglish(locale)
|
||
? "Uses instability and lifted-index structure."
|
||
: "结合不稳定能量与抬升指数判断。",
|
||
tone:
|
||
upperAirSignal.trigger_risk === "high"
|
||
? "cold"
|
||
: upperAirSignal.trigger_risk === "low"
|
||
? "warm"
|
||
: "",
|
||
value:
|
||
upperAirSignal.trigger_risk === "high"
|
||
? isEnglish(locale)
|
||
? "High"
|
||
: "高"
|
||
: upperAirSignal.trigger_risk === "medium"
|
||
? isEnglish(locale)
|
||
? "Medium"
|
||
: "中"
|
||
: isEnglish(locale)
|
||
? "Low"
|
||
: "低",
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Heating efficiency" : "冲高效率",
|
||
note:
|
||
upperAirSignal.boundary_layer_height_max != null
|
||
? isEnglish(locale)
|
||
? `How efficiently surface warmth can keep translating upward. Mixing depth peaks near ${Math.round(Number(upperAirSignal.boundary_layer_height_max))} m.`
|
||
: `看地面热量能不能持续往上送，决定冲高效率。混合层高度峰值约 ${Math.round(Number(upperAirSignal.boundary_layer_height_max))} 米。`
|
||
: isEnglish(locale)
|
||
? "Tracks daytime mixing depth."
|
||
: "跟踪白天混合层深度。",
|
||
tone:
|
||
upperAirSignal.mixing_strength === "strong"
|
||
? "warm"
|
||
: upperAirSignal.mixing_strength === "weak"
|
||
? "cold"
|
||
: "",
|
||
value:
|
||
upperAirSignal.mixing_strength === "strong"
|
||
? isEnglish(locale)
|
||
? "Strong"
|
||
: "强"
|
||
: upperAirSignal.mixing_strength === "medium"
|
||
? isEnglish(locale)
|
||
? "Medium"
|
||
: "中"
|
||
: isEnglish(locale)
|
||
? "Weak"
|
||
: "弱",
|
||
},
|
||
...(tafMetric ? [tafMetric] : []),
|
||
]
|
||
: tafMetric
|
||
? [tafMetric]
|
||
: [];
|
||
|
||
const futureSlice =
|
||
isTargetToday && currentMinutes !== null
|
||
? slice.filter((point) => {
|
||
const minutes = pointMinutes(point);
|
||
return minutes === null ? true : minutes >= currentMinutes;
|
||
})
|
||
: slice;
|
||
const untilSunsetSlice =
|
||
canUseSunsetWindow && sunsetMinutes !== null
|
||
? futureSlice.filter((point) => {
|
||
const minutes = pointMinutes(point);
|
||
return minutes === null ? false : minutes <= sunsetMinutes;
|
||
})
|
||
: futureSlice;
|
||
const aroundPeakSlice =
|
||
isTargetToday &&
|
||
peakWindowStartMinutes !== null &&
|
||
peakWindowEndMinutes !== null
|
||
? futureSlice.filter((point) => {
|
||
const minutes = pointMinutes(point);
|
||
return minutes === null
|
||
? false
|
||
: minutes >= peakWindowStartMinutes && minutes <= peakWindowEndMinutes;
|
||
})
|
||
: [];
|
||
const workingSlice =
|
||
aroundPeakSlice.length >= 2
|
||
? aroundPeakSlice
|
||
: untilSunsetSlice.length >= 2
|
||
? untilSunsetSlice
|
||
: futureSlice.length >= 2
|
||
? futureSlice
|
||
: slice;
|
||
const usingPeakWindow = aroundPeakSlice.length >= 2;
|
||
const usingSunsetWindow = canUseSunsetWindow && untilSunsetSlice.length >= 2;
|
||
const first = workingSlice[0] || slice[0];
|
||
const last = workingSlice[workingSlice.length - 1] || slice[slice.length - 1];
|
||
const effectiveHours = Math.max(1, workingSlice.length);
|
||
const windowLabel = `${first?.label || "--"}-${last?.label || "--"}`;
|
||
const windowText = isEnglish(locale)
|
||
? usingPeakWindow
|
||
? `today ${windowLabel} (~${effectiveHours}h, around peak window)`
|
||
: usingSunsetWindow
|
||
? `today ${windowLabel} (~${effectiveHours}h, now -> sunset)`
|
||
: isTargetToday
|
||
? `today ${windowLabel} (~${effectiveHours}h)`
|
||
: `daily ${windowLabel} (~${effectiveHours}h)`
|
||
: usingPeakWindow
|
||
? `今日 ${windowLabel}（约 ${effectiveHours} 小时，围绕峰值窗口）`
|
||
: usingSunsetWindow
|
||
? `今日 ${windowLabel}（约 ${effectiveHours} 小时，当前至日落）`
|
||
: isTargetToday
|
||
? `今日 ${windowLabel}（约 ${effectiveHours} 小时）`
|
||
: `当日日内 ${windowLabel}（约 ${effectiveHours} 小时）`;
|
||
const firstTemp = Number.isFinite(Number(first.temp)) ? Number(first.temp) : currentTemp;
|
||
const lastTemp = Number.isFinite(Number(last.temp)) ? Number(last.temp) : firstTemp;
|
||
const tempDelta =
|
||
Number.isFinite(firstTemp) && Number.isFinite(lastTemp) ? lastTemp - firstTemp : 0;
|
||
const firstDew = Number.isFinite(Number(first.dewPoint))
|
||
? Number(first.dewPoint)
|
||
: currentDew;
|
||
const lastDew = Number.isFinite(Number(last.dewPoint))
|
||
? Number(last.dewPoint)
|
||
: firstDew;
|
||
const dewDelta =
|
||
Number.isFinite(firstDew) && Number.isFinite(lastDew) ? lastDew - firstDew : 0;
|
||
const firstPressure = Number.isFinite(Number(first.pressure))
|
||
? Number(first.pressure)
|
||
: null;
|
||
const lastPressure = Number.isFinite(Number(last.pressure))
|
||
? Number(last.pressure)
|
||
: firstPressure;
|
||
const pressureDelta =
|
||
Number.isFinite(Number(firstPressure)) && Number.isFinite(Number(lastPressure))
|
||
? Number(lastPressure) - Number(firstPressure)
|
||
: 0;
|
||
const firstCloud = Number.isFinite(Number(first.cloudCover))
|
||
? Number(first.cloudCover)
|
||
: null;
|
||
const lastCloud = Number.isFinite(Number(last.cloudCover))
|
||
? Number(last.cloudCover)
|
||
: firstCloud;
|
||
const cloudDelta =
|
||
Number.isFinite(Number(firstCloud)) && Number.isFinite(Number(lastCloud))
|
||
? Number(lastCloud) - Number(firstCloud)
|
||
: 0;
|
||
const precipMax = slice.reduce(
|
||
(max, point) => Math.max(max, Number(point.precipProb) || 0),
|
||
0,
|
||
);
|
||
const precipWindowSource =
|
||
futureSlice.length >= 2 ? futureSlice : slice;
|
||
const precipCandidates = precipWindowSource
|
||
.map((point) => ({
|
||
label: normalizeHm(point.label),
|
||
minute: pointMinutes(point),
|
||
precip: Number(point.precipProb) || 0,
|
||
}))
|
||
.filter(
|
||
(point): point is { label: string; minute: number; precip: number } =>
|
||
point.label != null && point.minute != null,
|
||
);
|
||
const precipThreshold = precipMax >= 70 ? 50 : precipMax >= 40 ? 40 : 0;
|
||
const precipWindows: Array<{
|
||
start: number;
|
||
end: number;
|
||
startLabel: string;
|
||
endLabel: string;
|
||
peak: number;
|
||
}> = [];
|
||
if (precipThreshold > 0) {
|
||
let active:
|
||
| {
|
||
start: number;
|
||
end: number;
|
||
startLabel: string;
|
||
endLabel: string;
|
||
peak: number;
|
||
}
|
||
| null = null;
|
||
for (const point of precipCandidates) {
|
||
if (point.precip >= precipThreshold) {
|
||
if (!active) {
|
||
active = {
|
||
start: point.minute,
|
||
end: point.minute,
|
||
startLabel: point.label,
|
||
endLabel: point.label,
|
||
peak: point.precip,
|
||
};
|
||
} else {
|
||
active.end = point.minute;
|
||
active.endLabel = point.label;
|
||
active.peak = Math.max(active.peak, point.precip);
|
||
}
|
||
} else if (active) {
|
||
precipWindows.push(active);
|
||
active = null;
|
||
}
|
||
}
|
||
if (active) precipWindows.push(active);
|
||
}
|
||
const primaryPrecipWindow =
|
||
precipWindows.length > 0
|
||
? [...precipWindows].sort((left, right) => {
|
||
if (right.peak !== left.peak) return right.peak - left.peak;
|
||
return (right.end - right.start) - (left.end - left.start);
|
||
})[0]
|
||
: null;
|
||
const precipWindowLabel = primaryPrecipWindow
|
||
? `${primaryPrecipWindow.startLabel}-${primaryPrecipWindow.endLabel}`
|
||
: "";
|
||
const precipPeakOverlap =
|
||
primaryPrecipWindow &&
|
||
peakWindowStartMinutes != null &&
|
||
peakWindowEndMinutes != null
|
||
? Math.max(
|
||
0,
|
||
Math.min(primaryPrecipWindow.end, peakWindowEndMinutes) -
|
||
Math.max(primaryPrecipWindow.start, peakWindowStartMinutes),
|
||
)
|
||
: 0;
|
||
const precipOverlapLevel =
|
||
primaryPrecipWindow && peakWindowStartMinutes != null && peakWindowEndMinutes != null
|
||
? precipPeakOverlap >= 120
|
||
? "high"
|
||
: precipPeakOverlap > 0
|
||
? "medium"
|
||
: "low"
|
||
: "unknown";
|
||
const precipWindowSummary = (() => {
|
||
if (!primaryPrecipWindow) {
|
||
return isEnglish(locale)
|
||
? "No concentrated model precipitation window is visible yet."
|
||
: "模型里暂时还看不出明显集中的降水窗口。";
|
||
}
|
||
const overlapText = isEnglish(locale)
|
||
? precipOverlapLevel === "high"
|
||
? "It overlaps heavily with the peak window."
|
||
: precipOverlapLevel === "medium"
|
||
? "It overlaps part of the peak window."
|
||
: "It sits mostly outside the peak window."
|
||
: precipOverlapLevel === "high"
|
||
? "与峰值窗口重叠较高。"
|
||
: precipOverlapLevel === "medium"
|
||
? "与峰值窗口部分重叠。"
|
||
: "主要落在峰值窗口之外。";
|
||
return isEnglish(locale)
|
||
? `Model precipitation window is ${precipWindowLabel}, peaking near ${Math.round(primaryPrecipWindow.peak)}%. ${overlapText}`
|
||
: `模型降水窗口在 ${precipWindowLabel}，峰值约 ${Math.round(primaryPrecipWindow.peak)}%。${overlapText}`;
|
||
})();
|
||
const firstBucket = trendBucketFromDir(first.windDir);
|
||
const lastBucket = trendBucketFromDir(last.windDir);
|
||
const weatherGovPeriods = getForecastTextForDate(detail, dateStr);
|
||
const weatherGovText = weatherGovPeriods
|
||
.map(
|
||
(period) =>
|
||
`${period.short_forecast || ""} ${period.detailed_forecast || ""}`.toLowerCase(),
|
||
)
|
||
.join(" ");
|
||
|
||
let warmScore = 0;
|
||
let coldScore = 0;
|
||
if (tempDelta >= 2) warmScore += 24;
|
||
else if (tempDelta >= 0.8) warmScore += 12;
|
||
if (tempDelta <= -2) coldScore += 24;
|
||
else if (tempDelta <= -0.8) coldScore += 12;
|
||
if (dewDelta >= 1.2) warmScore += 14;
|
||
if (dewDelta <= -1.2) coldScore += 10;
|
||
if (pressureDelta >= 1.2) coldScore += 16;
|
||
if (pressureDelta <= -1.0) warmScore += 8;
|
||
if (lastBucket === "southerly") warmScore += 14;
|
||
if (firstBucket !== lastBucket && lastBucket === "southerly") warmScore += 10;
|
||
if (lastBucket === "northerly") coldScore += 14;
|
||
if (firstBucket !== lastBucket && lastBucket === "northerly") coldScore += 10;
|
||
if (cloudDelta >= 15 && tempDelta >= 0) warmScore += 6;
|
||
if (cloudDelta >= 15 && tempDelta < 0) coldScore += 8;
|
||
if (precipMax >= 40) coldScore += 8;
|
||
if (
|
||
weatherGovText.includes("cold front") ||
|
||
weatherGovText.includes("temperatures falling")
|
||
) {
|
||
coldScore += 18;
|
||
}
|
||
if (weatherGovText.includes("warm front") || weatherGovText.includes("warmer")) {
|
||
warmScore += 18;
|
||
}
|
||
if (weatherGovText.includes("thunder") || weatherGovText.includes("snow")) {
|
||
coldScore += 8;
|
||
}
|
||
|
||
const score = Math.max(-100, Math.min(100, warmScore - coldScore));
|
||
const warmLabel = isEnglish(locale) ? "Near-term warming bias" : "未来偏升温";
|
||
const coldLabel = isEnglish(locale) ? "Near-term cooling bias" : "未来偏降温";
|
||
const monitorLabel = isEnglish(locale) ? "Direction unclear" : "方向不清";
|
||
const label = score >= 18 ? warmLabel : score <= -18 ? coldLabel : monitorLabel;
|
||
const confidence =
|
||
Math.abs(score) >= 45 ? "high" : Math.abs(score) >= 22 ? "medium" : "low";
|
||
const directionalLead = (() => {
|
||
if (isEnglish(locale)) {
|
||
if (score >= 18 && tempDelta >= 0.5) {
|
||
return `Over ${windowText}, temperatures still lean warmer.`;
|
||
}
|
||
if (score <= -18 && tempDelta <= -0.5) {
|
||
return `Over ${windowText}, temperatures still lean cooler.`;
|
||
}
|
||
if (score >= 18) {
|
||
return `Over ${windowText}, the structure still leans warmer, but the warming pace is not strong yet.`;
|
||
}
|
||
if (score <= -18) {
|
||
return `Over ${windowText}, the structure still leans cooler, but the cooling pace is not decisive yet.`;
|
||
}
|
||
if (tempDelta >= 0.8) {
|
||
return `Over ${windowText}, temperatures still lean warmer, but confidence is limited.`;
|
||
}
|
||
if (tempDelta <= -0.8) {
|
||
return `Over ${windowText}, temperatures still lean cooler, but confidence is limited.`;
|
||
}
|
||
return `Over ${windowText}, temperatures are more likely to stay range-bound for now.`;
|
||
}
|
||
|
||
if (score >= 18 && tempDelta >= 0.5) {
|
||
return `${windowText}偏增温，后续更可能继续往上走。`;
|
||
}
|
||
if (score <= -18 && tempDelta <= -0.5) {
|
||
return `${windowText}偏降温，后续更可能继续往下走。`;
|
||
}
|
||
if (score >= 18) {
|
||
return `${windowText}仍偏增温，但增温兑现力度暂时不算强。`;
|
||
}
|
||
if (score <= -18) {
|
||
return `${windowText}仍偏降温，但降温兑现力度暂时不算强。`;
|
||
}
|
||
if (tempDelta >= 0.8) {
|
||
return `${windowText}略偏增温，但结构信号置信度有限。`;
|
||
}
|
||
if (tempDelta <= -0.8) {
|
||
return `${windowText}略偏降温，但结构信号置信度有限。`;
|
||
}
|
||
return `${windowText}更像震荡整理，短时升降温方向暂不清晰。`;
|
||
})();
|
||
const summary = (() => {
|
||
const parts: string[] = [];
|
||
|
||
if (isEnglish(locale)) {
|
||
parts.push(directionalLead);
|
||
|
||
if (lastBucket === "southerly" && firstBucket !== "southerly") {
|
||
parts.push("Low-level wind turns more southerly.");
|
||
} else if (lastBucket === "northerly" && firstBucket !== "northerly") {
|
||
parts.push("Low-level wind shifts toward a northerly regime.");
|
||
}
|
||
|
||
if (tempDelta >= 0.8) {
|
||
parts.push(`Temperature rises by ${formatDelta(tempDelta, detail.temp_symbol)}.`);
|
||
} else if (tempDelta <= -0.8) {
|
||
parts.push(`Temperature eases by ${formatDelta(tempDelta, detail.temp_symbol)}.`);
|
||
}
|
||
|
||
if (dewDelta >= 0.8) {
|
||
parts.push("Dew point is lifting, suggesting moisture transport is strengthening.");
|
||
} else if (dewDelta <= -0.8) {
|
||
parts.push("Dew point is falling, so low-level air is turning drier.");
|
||
}
|
||
|
||
if (cloudDelta >= 15) {
|
||
parts.push("Cloud cover is building.");
|
||
} else if (cloudDelta <= -15) {
|
||
parts.push("Cloud cover is easing.");
|
||
}
|
||
|
||
if (pressureDelta >= 1) {
|
||
parts.push("Pressure rebound argues for a cooler push.");
|
||
} else if (pressureDelta <= -1) {
|
||
parts.push("Pressure is softening, which is less hostile to warming.");
|
||
}
|
||
|
||
if (precipMax >= 50) {
|
||
parts.push(
|
||
primaryPrecipWindow
|
||
? `Model precipitation risk concentrates in ${precipWindowLabel}.`
|
||
: "Precipitation risk is high enough to watch for cloud/rain suppression.",
|
||
);
|
||
}
|
||
|
||
if (!parts.length) {
|
||
parts.push(`Structured trend is mixed, so the core judgement still centers on ${windowText}.`);
|
||
} else {
|
||
parts.push(`Core judgement remains focused on ${windowText}.`);
|
||
}
|
||
} else {
|
||
parts.push(directionalLead);
|
||
|
||
if (lastBucket === "southerly" && firstBucket !== "southerly") {
|
||
parts.push("低层风向更偏南，暖空气输送权重上升。");
|
||
} else if (lastBucket === "northerly" && firstBucket !== "northerly") {
|
||
parts.push("低层风向转偏北，冷空气影响权重上升。");
|
||
}
|
||
|
||
if (tempDelta >= 0.8) {
|
||
parts.push(`气温抬升 ${formatDelta(tempDelta, detail.temp_symbol)}。`);
|
||
} else if (tempDelta <= -0.8) {
|
||
parts.push(`气温回落 ${formatDelta(tempDelta, detail.temp_symbol)}。`);
|
||
}
|
||
|
||
if (dewDelta >= 0.8) {
|
||
parts.push("露点同步上升，说明暖湿输送在增强。");
|
||
} else if (dewDelta <= -0.8) {
|
||
parts.push("露点回落，低层空气在转干。");
|
||
}
|
||
|
||
if (cloudDelta >= 15) {
|
||
parts.push("云量正在增多。");
|
||
} else if (cloudDelta <= -15) {
|
||
parts.push("云量正在回落。");
|
||
}
|
||
|
||
if (pressureDelta >= 1) {
|
||
parts.push("气压回升，更偏向冷空气压入。");
|
||
} else if (pressureDelta <= -1) {
|
||
parts.push("气压走低，对增温压制减弱。");
|
||
}
|
||
|
||
if (precipMax >= 50) {
|
||
parts.push(
|
||
primaryPrecipWindow
|
||
? `模型降水窗口主要落在 ${precipWindowLabel}。`
|
||
: "降水概率已足以关注云雨压温。",
|
||
);
|
||
}
|
||
|
||
if (!parts.length) {
|
||
parts.push(`结构信号分化较大，核心仍围绕${windowText}观察。`);
|
||
} else {
|
||
parts.push(`核心判断窗口仍以${windowText}为主。`);
|
||
}
|
||
}
|
||
|
||
return parts.join(isEnglish(locale) ? " " : "");
|
||
})();
|
||
const tafContrastSummary =
|
||
tafSignal.available && dateStr === detail.local_date
|
||
? (() => {
|
||
const tafSuppression = String(
|
||
tafSignal.suppression_level || "low",
|
||
).toLowerCase();
|
||
const isCoolingBias = score <= -18;
|
||
const isWarmingBias = score >= 18;
|
||
|
||
if (tafSuppression === "low" && isCoolingBias) {
|
||
return isEnglish(locale)
|
||
? "TAF is not adding a new cloud/rain suppression signal, but the near-surface window is already leaning cooler, so the current cooling bias still comes mainly from surface structure."
|
||
: "TAF 没有新增云雨压温利空，但当前峰值窗口里的近地面结构已经偏弱，所以这次偏降温判断仍主要来自近地面信号。";
|
||
}
|
||
if (tafSuppression === "low" && isWarmingBias) {
|
||
return isEnglish(locale)
|
||
? "TAF is not adding a new cloud/rain cap, and the warmer bias still comes mainly from the surface window."
|
||
: "TAF 没有新增云雨压温约束，当前偏升温判断仍主要来自近地面窗口。";
|
||
}
|
||
if (tafSuppression === "medium" && isCoolingBias) {
|
||
return isEnglish(locale)
|
||
? "TAF is not the only driver here; it only reinforces part of the cooling-side case, while the main tilt still comes from the surface window."
|
||
: "这次偏降温不只是 TAF 在起作用；TAF 只是加强了部分冷侧判断，主方向仍来自近地面窗口。";
|
||
}
|
||
return "";
|
||
})()
|
||
: "";
|
||
const tafSummaryLineBody = [
|
||
tafPrimarySummary,
|
||
tafReferenceSummary,
|
||
tafFallbackSummary,
|
||
tafContrastSummary,
|
||
]
|
||
.filter(Boolean)
|
||
.join(isEnglish(locale) ? " " : "");
|
||
const surfaceSummaryLine = summary
|
||
? isEnglish(locale)
|
||
? `Surface: ${summary}`
|
||
: `近地面：${summary}`
|
||
: "";
|
||
const tafSummaryLine = tafSummaryLineBody
|
||
? isEnglish(locale)
|
||
? `Airport TAF: ${tafSummaryLineBody}`
|
||
: `机场 TAF：${tafSummaryLineBody}`
|
||
: "";
|
||
const summaryLines = [surfaceSummaryLine, tafSummaryLine].filter(Boolean);
|
||
const combinedSummary = summaryLines.join(isEnglish(locale) ? " " : "");
|
||
const cloudNote = (() => {
|
||
if (cloudDelta >= 15 && tempDelta >= 0.8 && dewDelta >= 0.8) {
|
||
return isEnglish(locale)
|
||
? "Clouds are increasing while temperature and dew point still rise; this usually fits ongoing warm-moist transport rather than immediate cooling."
|
||
: "云量上升时温度和露点仍在抬升，更像暖湿输送持续中，而不是立刻转凉。";
|
||
}
|
||
if (cloudDelta >= 15 && tempDelta >= 0 && lastBucket === "southerly") {
|
||
return isEnglish(locale)
|
||
? "Clouds are building without clear cooling, and the low-level wind still leans southerly; watch for warm advection to continue."
|
||
: "云量增多但未明显降温，且低层风仍偏南，需继续关注暖平流是否延续。";
|
||
}
|
||
if (cloudDelta >= 15 && tempDelta < 0 && precipMax >= 40) {
|
||
return isEnglish(locale)
|
||
? "Clouds are thickening while temperature eases and precipitation risk is elevated; cloud/rain suppression is becoming more likely."
|
||
: "云量增厚且气温回落，同时降水概率偏高，更像云雨压温开始生效。";
|
||
}
|
||
if (cloudDelta >= 15 && tempDelta < 0 && pressureDelta >= 1) {
|
||
return isEnglish(locale)
|
||
? "Clouds are increasing while temperature softens and pressure rebounds; watch for cold-air push or frontal suppression."
|
||
: "云量上升同时气温走弱、气压回升，需留意冷空气压入或锋面压温。";
|
||
}
|
||
if (cloudDelta <= -15 && tempDelta >= 0.8) {
|
||
return isEnglish(locale)
|
||
? "Cloud cover is easing while temperature rises; daytime heating efficiency is improving."
|
||
: "云量回落且温度抬升，白天增温效率在改善。";
|
||
}
|
||
return isEnglish(locale)
|
||
? "Read forecast cloud-cover increase together with temperature, dew point, wind, and precipitation; it does not override the current observed sky condition."
|
||
: "这里显示的是预测窗口内的云量增幅，需要结合温度、露点、风向和降水一起看，不能覆盖当前实况的天空状况。";
|
||
})();
|
||
const dewNote = (() => {
|
||
if (dewDelta >= 1.2 && tempDelta >= 0.8) {
|
||
return isEnglish(locale)
|
||
? "Dew point and temperature rise together, which usually supports strengthening warm-moist transport."
|
||
: "露点和温度同步抬升，更偏向暖湿输送增强。";
|
||
}
|
||
if (dewDelta >= 1.2 && precipMax >= 40) {
|
||
return isEnglish(locale)
|
||
? "Moisture is building while precipitation risk is already notable; watch for showers to cap daytime heating."
|
||
: "水汽在累积且降水风险已抬升，需关注阵雨对午后增温的压制。";
|
||
}
|
||
if (dewDelta <= -1.2 && tempDelta <= 0) {
|
||
return isEnglish(locale)
|
||
? "Drier low-level air is arriving together with softer temperature, which leans away from warm-moist support."
|
||
: "低层空气在转干且温度偏弱，暖湿支撑正在减弱。";
|
||
}
|
||
return isEnglish(locale)
|
||
? "Use dew-point change to judge whether low-level warm-moist transport is strengthening or fading."
|
||
: "露点变化主要用于判断低层暖湿输送是在增强还是减弱。";
|
||
})();
|
||
const pressureNote = (() => {
|
||
if (pressureDelta >= 1.2 && tempDelta <= -0.8) {
|
||
return isEnglish(locale)
|
||
? "Pressure rebound with cooling usually points to a cooler push or frontal suppression."
|
||
: "气压回升且温度走弱，更像冷空气压入或锋面压温。";
|
||
}
|
||
if (pressureDelta <= -1.0 && tempDelta >= 0.8) {
|
||
return isEnglish(locale)
|
||
? "Pressure is softening while temperature rises, a setup less hostile to warming."
|
||
: "气压走低同时温度抬升，对增温的压制相对减弱。";
|
||
}
|
||
return isEnglish(locale)
|
||
? "Pressure change is used as a supporting signal for cold-air push versus warming resilience."
|
||
: "气压变化更适合作为冷空气压入或增温韧性的辅助判断。";
|
||
})();
|
||
const windNote = (() => {
|
||
if (firstBucket !== lastBucket && lastBucket === "southerly") {
|
||
return isEnglish(locale)
|
||
? "Wind turns toward a southerly regime, which is more favorable for warming."
|
||
: "风向转偏南，更有利于增温。";
|
||
}
|
||
if (firstBucket !== lastBucket && lastBucket === "northerly") {
|
||
return isEnglish(locale)
|
||
? "Wind turns toward a northerly regime, which is more favorable for cooling."
|
||
: "风向转偏北，更有利于降温。";
|
||
}
|
||
if (lastBucket === "southerly") {
|
||
return isEnglish(locale)
|
||
? "Low-level flow remains southerly, so warm advection has not been disrupted."
|
||
: "低层风维持偏南，暖平流支撑尚未被破坏。";
|
||
}
|
||
if (lastBucket === "northerly") {
|
||
return isEnglish(locale)
|
||
? "Low-level flow remains northerly, so cooling-side support is still present."
|
||
: "低层风维持偏北，降温侧支撑仍在。";
|
||
}
|
||
return isEnglish(locale)
|
||
? "Wind-direction change matters most when it crosses into southerly or northerly buckets."
|
||
: "风向变化最关键的是是否跨入偏南或偏北风桶。";
|
||
})();
|
||
const precipNote = (() => {
|
||
if (precipMax >= 60) {
|
||
return isEnglish(locale)
|
||
? `${precipWindowSummary} Cloud/rain suppression can materially change the peak outcome.`
|
||
: `${precipWindowSummary} 降水风险已高到足以显著改变峰值兑现结果，需要重点防压温。`;
|
||
}
|
||
if (precipMax >= 40) {
|
||
return isEnglish(locale)
|
||
? `${precipWindowSummary} Watch whether cloud and showers interrupt daytime heating.`
|
||
: `${precipWindowSummary} 需要关注云系和阵雨是否打断白天增温。`;
|
||
}
|
||
return isEnglish(locale)
|
||
? "Precipitation risk remains limited and is used mainly as a suppression check."
|
||
: "降水风险暂时有限，主要作为压温风险校验项。";
|
||
})();
|
||
|
||
const metrics = [
|
||
{
|
||
label: isEnglish(locale) ? "Temperature delta" : "温度变化",
|
||
note: isEnglish(locale)
|
||
? `Official Open-Meteo hourly data; window: ${windowText}`
|
||
: `官方 Open-Meteo 小时数据；计算窗口：${windowText}`,
|
||
tone: tempDelta >= 0.8 ? "warm" : tempDelta <= -0.8 ? "cold" : "",
|
||
value: formatDelta(tempDelta, detail.temp_symbol),
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Dew point delta" : "露点变化",
|
||
note: dewNote,
|
||
tone: dewDelta >= 0.8 ? "warm" : dewDelta <= -0.8 ? "cold" : "",
|
||
value: formatDelta(dewDelta, detail.temp_symbol),
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Pressure delta" : "气压变化",
|
||
note: pressureNote,
|
||
tone: pressureDelta >= 1 ? "cold" : pressureDelta <= -1 ? "warm" : "",
|
||
value: formatDelta(pressureDelta, " hPa"),
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Wind-direction evolution" : "风向演变",
|
||
note: windNote,
|
||
value: `${bucketLabel(firstBucket, locale)} -> ${bucketLabel(lastBucket, locale)}`,
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Precip window" : "降水窗口",
|
||
note: precipNote,
|
||
tone: precipMax >= 50 ? "cold" : "",
|
||
value: primaryPrecipWindow
|
||
? `${precipWindowLabel} · ${Math.round(precipMax)}%`
|
||
: `${Math.round(precipMax)}%`,
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Forecast cloud-cover delta" : "预测云量增幅",
|
||
note: cloudNote,
|
||
tone:
|
||
cloudDelta >= 15 && tempDelta >= 0
|
||
? "warm"
|
||
: cloudDelta >= 15 && tempDelta < 0
|
||
? "cold"
|
||
: "",
|
||
value: formatDelta(cloudDelta, "%"),
|
||
},
|
||
];
|
||
|
||
if (backendNotes.length) {
|
||
const normalizedSummary = backendSummary.trim();
|
||
const alignedNotes = backendNotes.filter(
|
||
(note) => String(note || "").trim() !== normalizedSummary,
|
||
);
|
||
alignedNotes.slice(0, metrics.length).forEach((note, index) => {
|
||
if (!note) return;
|
||
metrics[index] = {
|
||
...metrics[index],
|
||
note,
|
||
};
|
||
});
|
||
}
|
||
|
||
return {
|
||
confidence,
|
||
label,
|
||
metrics,
|
||
upperAirMetrics,
|
||
upperAirSummary,
|
||
precipOverlapLevel,
|
||
precipWindowLabel,
|
||
precipMax,
|
||
score,
|
||
summary: combinedSummary || backendSummary || summary,
|
||
summaryLines,
|
||
weatherGovPeriods,
|
||
};
|
||
}
|
||
|
||
export function getFutureModalView(
|
||
detail: CityDetail,
|
||
dateStr: string,
|
||
locale: Locale = "zh-CN",
|
||
) {
|
||
const forecastEntry =
|
||
detail.forecast?.daily?.find((item) => item.date === dateStr) || null;
|
||
const dailyModel = detail.multi_model_daily?.[dateStr] || {};
|
||
const probabilities = dailyModel.probabilities || [];
|
||
const totalProbability = probabilities.reduce((sum, item) => {
|
||
const probability = Number(item.probability);
|
||
return Number.isFinite(probability) ? sum + probability : sum;
|
||
}, 0);
|
||
const weightedProbability = probabilities.reduce((sum, item) => {
|
||
const value = Number(item.value);
|
||
const probability = Number(item.probability);
|
||
if (!Number.isFinite(value) || !Number.isFinite(probability)) {
|
||
return sum;
|
||
}
|
||
return sum + value * probability;
|
||
}, 0);
|
||
const mu = totalProbability > 0 ? weightedProbability / totalProbability : null;
|
||
const deb = dailyModel.deb?.prediction ?? forecastEntry?.max_temp ?? null;
|
||
|
||
return {
|
||
deb,
|
||
forecastEntry,
|
||
front: computeFrontTrendSignal(detail, dateStr, locale),
|
||
models: dailyModel.models || {},
|
||
mu: Number.isFinite(Number(mu)) ? Number(mu) : null,
|
||
probabilities,
|
||
slice: getFutureSlice(detail, dateStr),
|
||
};
|
||
}
|
||
|
||
export function getShortTermNowcastLines(
|
||
detail: CityDetail,
|
||
dateStr: string,
|
||
locale: Locale = "zh-CN",
|
||
) {
|
||
const slice = getFutureSlice(detail, dateStr);
|
||
if (dateStr !== detail.local_date) {
|
||
const afternoon = slice.filter((point) => {
|
||
const hour = Number.parseInt(String(point.label).split(":")[0], 10);
|
||
return Number.isFinite(hour) && hour >= 12 && hour <= 18;
|
||
});
|
||
const target = afternoon.length ? afternoon : slice;
|
||
if (!target.length) {
|
||
return [
|
||
[isEnglish(locale) ? "Target date" : "目标日期", dateStr],
|
||
[
|
||
isEnglish(locale) ? "Peak window" : "峰值窗口",
|
||
isEnglish(locale)
|
||
? "No sufficient hourly forecast data for target-day peak-window diagnostics."
|
||
: "暂无足够的小时级 forecast 数据，无法生成目标日午后峰值窗口判断。",
|
||
],
|
||
] as const;
|
||
}
|
||
|
||
const maxIndex = target.reduce((bestIndex, point, index, array) => {
|
||
const temp = Number(point.temp);
|
||
const bestTemp = Number(array[bestIndex]?.temp);
|
||
if (!Number.isFinite(temp)) return bestIndex;
|
||
if (!Number.isFinite(bestTemp) || temp > bestTemp) return index;
|
||
return bestIndex;
|
||
}, 0);
|
||
|
||
const peakSlice = target.slice(
|
||
Math.max(0, maxIndex - 1),
|
||
Math.min(target.length, maxIndex + 2),
|
||
);
|
||
const start = peakSlice[0];
|
||
const end = peakSlice[peakSlice.length - 1];
|
||
const peakPoint = target[maxIndex] || end;
|
||
const startTemp = Number(start.temp);
|
||
const endTemp = Number(end.temp);
|
||
const startDew = Number(start.dewPoint);
|
||
const endDew = Number(end.dewPoint);
|
||
const startPressure = Number(start.pressure);
|
||
const endPressure = Number(end.pressure);
|
||
const precipValues = peakSlice
|
||
.map((point) => Number(point.precipProb))
|
||
.filter(Number.isFinite);
|
||
const cloudValues = peakSlice
|
||
.map((point) => Number(point.cloudCover))
|
||
.filter(Number.isFinite);
|
||
const maxPrecip = precipValues.length ? Math.max(...precipValues) : 0;
|
||
const maxCloud = cloudValues.length ? Math.max(...cloudValues) : 0;
|
||
|
||
return [
|
||
[isEnglish(locale) ? "Target date" : "目标日期", dateStr],
|
||
[
|
||
isEnglish(locale) ? "Peak window" : "峰值窗口",
|
||
isEnglish(locale)
|
||
? `${start.label} - ${end.label} (prefer 12:00-18:00)`
|
||
: `${start.label} - ${end.label}（优先取 12:00-18:00）`,
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Peak estimate" : "峰值预估",
|
||
`${Number.isFinite(Number(peakPoint.temp)) ? Number(peakPoint.temp).toFixed(1) : "--"}${detail.temp_symbol} @ ${peakPoint.label || "--"}`,
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Window temperature" : "窗口温度",
|
||
`${Number.isFinite(startTemp) ? startTemp.toFixed(1) : "--"}${detail.temp_symbol} -> ${Number.isFinite(endTemp) ? endTemp.toFixed(1) : "--"}${detail.temp_symbol} (${formatDelta(endTemp - startTemp, detail.temp_symbol)})`,
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Dew-point delta" : "露点变化",
|
||
isEnglish(locale)
|
||
? `${formatDelta(endDew - startDew, detail.temp_symbol)} for diagnosing warm/wet transport in afternoon.`
|
||
: `${formatDelta(endDew - startDew, detail.temp_symbol)}，用于判断午后暖湿输送是否增强。`,
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Wind shift" : "风向演变",
|
||
isEnglish(locale)
|
||
? `${bucketLabel(trendBucketFromDir(start.windDir), locale)} -> ${bucketLabel(trendBucketFromDir(end.windDir), locale)} around peak window.`
|
||
: `${bucketLabel(trendBucketFromDir(start.windDir), locale)} -> ${bucketLabel(trendBucketFromDir(end.windDir), locale)}，关注峰值前后是否转南风或回摆北风。`,
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Pressure delta" : "气压变化",
|
||
isEnglish(locale)
|
||
? `${formatDelta(endPressure - startPressure, " hPa")} (higher pressure usually favors cold-air push).`
|
||
: `${formatDelta(endPressure - startPressure, " hPa")}，上升更偏向冷空气压入。`,
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Precip / cloud" : "降水 / 云量",
|
||
isEnglish(locale)
|
||
? `${Math.round(maxPrecip)}% / ${Math.round(maxCloud)}% for cloud-suppression judgement around peak hours.`
|
||
: `${Math.round(maxPrecip)}% / ${Math.round(maxCloud)}%，用于判断峰值时段是否受云系压制。`,
|
||
],
|
||
] as const;
|
||
}
|
||
|
||
const recent = Array.isArray(detail.metar_recent_obs)
|
||
? detail.metar_recent_obs.slice(-4)
|
||
: [];
|
||
const nearby = Array.isArray(detail.official_nearby) && detail.official_nearby.length
|
||
? detail.official_nearby
|
||
: Array.isArray(detail.mgm_nearby)
|
||
? detail.mgm_nearby
|
||
: [];
|
||
const nearbySource = String(detail.nearby_source || "").toLowerCase();
|
||
const sourceLabel =
|
||
nearbySource === "mgm" || isTurkishMgmCity(detail)
|
||
? isEnglish(locale)
|
||
? "MGM nearby stations"
|
||
: "MGM 周边站"
|
||
: nearbySource === "official_cluster"
|
||
? isEnglish(locale)
|
||
? "Official nearby stations"
|
||
: "官方周边站"
|
||
: isEnglish(locale)
|
||
? "METAR nearby stations"
|
||
: "METAR 周边站";
|
||
const currentTemp = Number(detail.current?.temp);
|
||
const recentTemps = recent
|
||
.map((point) => Number(point.temp))
|
||
.filter((value) => Number.isFinite(value));
|
||
const baseline = recentTemps.length ? recentTemps[0] : currentTemp;
|
||
const shortDelta =
|
||
Number.isFinite(currentTemp) && Number.isFinite(baseline)
|
||
? currentTemp - baseline
|
||
: 0;
|
||
let nearbyLead: { diff: number; name: string; temp: number; syncText: string } | null = null;
|
||
|
||
for (const station of nearby) {
|
||
const temp = Number(station.temp);
|
||
if (station.usable_for_intraday === false) continue;
|
||
if (!Number.isFinite(temp) || !Number.isFinite(currentTemp)) continue;
|
||
const diff = temp - currentTemp;
|
||
const syncStatus = String(station.sync_status || "").toLowerCase();
|
||
const syncDelta = Number(station.time_delta_vs_anchor_minutes);
|
||
const syncText =
|
||
syncStatus === "synced"
|
||
? isEnglish(locale)
|
||
? "time-synced"
|
||
: "时间同步"
|
||
: syncStatus === "near_realtime" || syncStatus === "lagged"
|
||
? Number.isFinite(syncDelta)
|
||
? isEnglish(locale)
|
||
? `${Math.round(syncDelta)} min offset`
|
||
: `时间差 ${Math.round(syncDelta)} 分钟`
|
||
: isEnglish(locale)
|
||
? "not fully synchronized"
|
||
: "非完全同步"
|
||
: syncStatus === "unknown"
|
||
? isEnglish(locale)
|
||
? "timing unverified"
|
||
: "时间待校验"
|
||
: "";
|
||
if (!nearbyLead || Math.abs(diff) > Math.abs(nearbyLead.diff)) {
|
||
nearbyLead = {
|
||
diff,
|
||
name:
|
||
station.name ||
|
||
station.icao ||
|
||
(isEnglish(locale) ? "Nearby station" : "周边站"),
|
||
temp,
|
||
syncText,
|
||
};
|
||
}
|
||
}
|
||
const usableNearbyCount = nearby.filter((station) => station.usable_for_intraday !== false).length;
|
||
|
||
const rows: Array<readonly [string, string]> = [
|
||
[
|
||
isEnglish(locale) ? "Primary station" : "当前主站",
|
||
`${detail.current?.temp ?? "--"}${detail.temp_symbol} @ ${detail.current?.obs_time || "--"}`,
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Raw METAR" : "原始 METAR",
|
||
detail.current?.raw_metar || (isEnglish(locale) ? "N/A" : "暂无"),
|
||
],
|
||
[
|
||
isEnglish(locale) ? "Next 0-2h" : "近 0-2 小时",
|
||
isEnglish(locale)
|
||
? `${formatDelta(shortDelta, detail.temp_symbol)} based on latest METAR sequence short-term momentum.`
|
||
: `${formatDelta(shortDelta, detail.temp_symbol)}，依据最近 METAR 序列判断短时动量。`,
|
||
],
|
||
[
|
||
sourceLabel,
|
||
isEnglish(locale)
|
||
? `${usableNearbyCount}/${nearby.length} stations usable for the nearby scan; station timestamps may differ.`
|
||
: `${usableNearbyCount}/${nearby.length} 个站点可参与邻近监控；周边站观测时间可能不同步。`,
|
||
],
|
||
];
|
||
|
||
if (nearbyLead) {
|
||
const tone = isEnglish(locale)
|
||
? nearbyLead.diff > 0
|
||
? "warmer"
|
||
: nearbyLead.diff < 0
|
||
? "cooler"
|
||
: "flat"
|
||
: nearbyLead.diff > 0
|
||
? "偏暖"
|
||
: nearbyLead.diff < 0
|
||
? "偏冷"
|
||
: "持平";
|
||
rows.push([
|
||
isEnglish(locale) ? "Leading station" : "领先站",
|
||
isEnglish(locale)
|
||
? `${nearbyLead.name} ${nearbyLead.temp}${detail.temp_symbol}, relative to primary station ${formatDelta(nearbyLead.diff, detail.temp_symbol)} (${tone})${nearbyLead.syncText ? `; ${nearbyLead.syncText}` : ""}.`
|
||
: `${nearbyLead.name} ${nearbyLead.temp}${detail.temp_symbol}，相对主站 ${formatDelta(nearbyLead.diff, detail.temp_symbol)}（${tone}）${nearbyLead.syncText ? `；${nearbyLead.syncText}` : ""}。`,
|
||
]);
|
||
}
|
||
|
||
return rows;
|
||
}
|
||
|
||
export function getHistorySummary(
|
||
history: HistoryPoint[],
|
||
cityLocalDate?: string | null,
|
||
) {
|
||
const toFinite = (value: unknown): number | null => {
|
||
const numeric = Number(value);
|
||
return Number.isFinite(numeric) ? numeric : null;
|
||
};
|
||
const isExcludedModel = (name: string) =>
|
||
String(name || "").toLowerCase().includes("meteoblue");
|
||
|
||
const cutoff = new Date();
|
||
cutoff.setHours(0, 0, 0, 0);
|
||
cutoff.setDate(cutoff.getDate() - 14);
|
||
|
||
const recentData = history.filter((row) => {
|
||
if (!row?.date) return false;
|
||
const rowDate = new Date(`${row.date}T00:00:00`);
|
||
return !Number.isNaN(rowDate.getTime()) && rowDate >= cutoff;
|
||
});
|
||
|
||
const settledData = recentData.filter((row) => {
|
||
if (!row?.date) return false;
|
||
return cityLocalDate
|
||
? row.date < cityLocalDate
|
||
: row.date < new Date().toISOString().slice(0, 10);
|
||
});
|
||
const comparableSettledData = settledData.filter((row) => {
|
||
const actual = toFinite(row.actual);
|
||
const deb = toFinite(row.deb);
|
||
return actual != null && deb != null;
|
||
});
|
||
|
||
let hits = 0;
|
||
const debErrors: number[] = [];
|
||
const modelErrors: Record<string, number[]> = {};
|
||
|
||
comparableSettledData.forEach((row) => {
|
||
const actual = toFinite(row.actual);
|
||
const deb = toFinite(row.deb);
|
||
if (actual == null || deb == null) return;
|
||
debErrors.push(Math.abs(actual - deb));
|
||
if (wuRound(actual) === wuRound(deb)) {
|
||
hits += 1;
|
||
}
|
||
|
||
const forecasts = row.forecasts || {};
|
||
Object.entries(forecasts).forEach(([modelName, modelValue]) => {
|
||
if (isExcludedModel(modelName)) return;
|
||
const mv = toFinite(modelValue);
|
||
if (actual == null || mv == null) return;
|
||
if (!modelErrors[modelName]) {
|
||
modelErrors[modelName] = [];
|
||
}
|
||
modelErrors[modelName].push(Math.abs(actual - mv));
|
||
});
|
||
});
|
||
|
||
const modelMaeList = Object.entries(modelErrors)
|
||
.map(([name, errors]) => ({
|
||
mae:
|
||
errors.length > 0
|
||
? errors.reduce((sum, value) => sum + value, 0) / errors.length
|
||
: Number.POSITIVE_INFINITY,
|
||
model: name,
|
||
sampleCount: errors.length,
|
||
}))
|
||
.filter((row) => Number.isFinite(row.mae) && row.sampleCount > 0)
|
||
.sort((a, b) => a.mae - b.mae);
|
||
|
||
const primaryModelMaeList = modelMaeList.filter((row) => row.sampleCount >= 2);
|
||
const bestModel = (primaryModelMaeList[0] || modelMaeList[0]) ?? null;
|
||
const bestModelName = bestModel?.model || null;
|
||
const bestModelMae = bestModel ? Number(bestModel.mae.toFixed(1)) : null;
|
||
const bestModelSeries = recentData.map((row) =>
|
||
bestModelName ? toFinite(row.forecasts?.[bestModelName]) : null,
|
||
);
|
||
|
||
let debWinDaysVsBest = 0;
|
||
let debVsBestComparableDays = 0;
|
||
if (bestModelName) {
|
||
comparableSettledData.forEach((row) => {
|
||
const actual = toFinite(row.actual);
|
||
const deb = toFinite(row.deb);
|
||
const bestModelVal = toFinite(row.forecasts?.[bestModelName]);
|
||
if (actual == null || deb == null || bestModelVal == null) return;
|
||
debVsBestComparableDays += 1;
|
||
if (Math.abs(deb - actual) <= Math.abs(bestModelVal - actual)) {
|
||
debWinDaysVsBest += 1;
|
||
}
|
||
});
|
||
}
|
||
|
||
const mgmSettledCount = settledData.reduce((count, row) => {
|
||
return toFinite(row.mgm) != null ? count + 1 : count;
|
||
}, 0);
|
||
const mgmSeriesComplete =
|
||
settledData.length >= 2 && mgmSettledCount === settledData.length;
|
||
const mgmSeries = mgmSeriesComplete
|
||
? recentData.map((row) => row.mgm ?? null)
|
||
: recentData.map(() => null);
|
||
|
||
return {
|
||
dates: recentData.map((row) => row.date),
|
||
debMae: debErrors.length
|
||
? Number(
|
||
(
|
||
debErrors.reduce((sum, value) => sum + value, 0) / debErrors.length
|
||
).toFixed(1),
|
||
)
|
||
: null,
|
||
debs: recentData.map((row) => row.deb),
|
||
bestModelName,
|
||
bestModelMae,
|
||
bestModelSeries,
|
||
modelMaeRanks: modelMaeList.map((row) => ({
|
||
model: row.model,
|
||
mae: Number(row.mae.toFixed(1)),
|
||
sampleCount: row.sampleCount,
|
||
})),
|
||
debWinDaysVsBest,
|
||
debVsBestComparableDays,
|
||
debWinRateVsBest:
|
||
debVsBestComparableDays > 0
|
||
? Number(((debWinDaysVsBest / debVsBestComparableDays) * 100).toFixed(0))
|
||
: null,
|
||
hitRate: debErrors.length
|
||
? Number(((hits / debErrors.length) * 100).toFixed(0))
|
||
: null,
|
||
mgmSeriesComplete,
|
||
mgms: mgmSeries,
|
||
recentData,
|
||
settledCount: comparableSettledData.length,
|
||
actuals: recentData.map((row) => row.actual),
|
||
};
|
||
}
|
||
|
||
function toFiniteNumber(value: unknown): number | null {
|
||
const numeric = Number(value);
|
||
return Number.isFinite(numeric) ? numeric : null;
|
||
}
|
||
|
||
function asRecord(value: unknown): Record<string, unknown> | null {
|
||
return value && typeof value === "object"
|
||
? (value as Record<string, unknown>)
|
||
: null;
|
||
}
|
||
|
||
function firstFiniteNumber(values: unknown[]) {
|
||
for (const value of values) {
|
||
const numeric = toFiniteNumber(value);
|
||
if (numeric != null) return numeric;
|
||
}
|
||
return null;
|
||
}
|
||
|
||
function firstNonEmptyString(values: unknown[]) {
|
||
for (const value of values) {
|
||
const text = String(value ?? "").trim();
|
||
if (text) return text;
|
||
}
|
||
return null;
|
||
}
|
||
|
||
function formatObservationUpdate(value: unknown, locale: Locale) {
|
||
const raw = String(value ?? "").trim();
|
||
if (!raw) return null;
|
||
|
||
const looksDated =
|
||
/^\d{4}-\d{2}-\d{2}/.test(raw) ||
|
||
raw.includes("T") ||
|
||
/[+-]\d{2}:?\d{2}$/.test(raw);
|
||
if (looksDated) {
|
||
const parsed = new Date(raw);
|
||
if (!Number.isNaN(parsed.getTime())) {
|
||
return new Intl.DateTimeFormat(isEnglish(locale) ? "en-US" : "zh-CN", {
|
||
day: "2-digit",
|
||
hour: "2-digit",
|
||
hour12: false,
|
||
minute: "2-digit",
|
||
month: "2-digit",
|
||
})
|
||
.format(parsed)
|
||
.replace(",", "");
|
||
}
|
||
}
|
||
|
||
return normalizeHm(raw) || raw;
|
||
}
|
||
|
||
function localObservationTimeCandidate(value: unknown) {
|
||
const raw = String(value ?? "").trim();
|
||
if (!raw || raw.includes("T") || /^\d{4}-\d{2}-\d{2}/.test(raw)) {
|
||
return "";
|
||
}
|
||
return normalizeHm(raw) || raw;
|
||
}
|
||
|
||
function getOfficialObservationCandidates(detail: CityDetail) {
|
||
const officialNearby = Array.isArray(detail.official_nearby)
|
||
? detail.official_nearby
|
||
: [];
|
||
const mgmNearby = Array.isArray(detail.mgm_nearby) ? detail.mgm_nearby : [];
|
||
const officialAnchor =
|
||
officialNearby.find(
|
||
(station) => station.is_settlement_anchor || station.is_airport_station,
|
||
) || officialNearby[0];
|
||
|
||
return {
|
||
centerStation: detail.center_station_candidate,
|
||
mgmNearby,
|
||
officialAnchor,
|
||
officialNearby,
|
||
};
|
||
}
|
||
|
||
function getObservedTemperatureProfile(detail: CityDetail, locale: Locale) {
|
||
const { mgmNearby } = getOfficialObservationCandidates(detail);
|
||
const currentSource = String(
|
||
detail.current?.settlement_source ||
|
||
detail.current?.settlement_source_label ||
|
||
"",
|
||
)
|
||
.trim()
|
||
.toLowerCase();
|
||
const isNmcCurrent = currentSource === "nmc" || currentSource.includes("nmc");
|
||
const isNmcAirport = String(detail.airport_primary?.source_label || "")
|
||
.trim()
|
||
.toLowerCase()
|
||
.includes("nmc");
|
||
const candidates = [
|
||
{
|
||
sourceLabel: detail.airport_current?.source_label || "METAR",
|
||
temp: detail.airport_current?.temp,
|
||
},
|
||
{
|
||
sourceLabel: detail.airport_primary?.source_label || "METAR",
|
||
temp: isNmcAirport ? null : detail.airport_primary?.temp,
|
||
},
|
||
{
|
||
sourceLabel: detail.current?.settlement_source_label,
|
||
temp: isNmcCurrent ? null : detail.current?.temp,
|
||
},
|
||
{
|
||
sourceLabel: mgmNearby[0]?.source_label,
|
||
temp: mgmNearby[0]?.temp,
|
||
},
|
||
];
|
||
const selected = candidates.find((candidate) =>
|
||
Number.isFinite(Number(candidate.temp)),
|
||
);
|
||
|
||
if (!selected) {
|
||
return isEnglish(locale) ? "Unavailable" : "未提供";
|
||
}
|
||
|
||
const observedTemp = Number(selected.temp);
|
||
const sourceLabel = firstNonEmptyString([
|
||
selected.sourceLabel,
|
||
getObservationSourceTag(detail),
|
||
]);
|
||
const rounded =
|
||
Math.abs(observedTemp - Math.round(observedTemp)) < 0.05
|
||
? String(Math.round(observedTemp))
|
||
: observedTemp.toFixed(1);
|
||
|
||
return `${rounded}${detail.temp_symbol || "°C"}${
|
||
sourceLabel ? ` · ${sourceLabel}` : ""
|
||
}`;
|
||
}
|
||
|
||
function getObservationUpdateProfile(detail: CityDetail, locale: Locale) {
|
||
const { mgmNearby } = getOfficialObservationCandidates(detail);
|
||
const mgmFirstRecord = asRecord(mgmNearby[0]);
|
||
const currentSource = String(
|
||
detail.current?.settlement_source ||
|
||
detail.current?.settlement_source_label ||
|
||
"",
|
||
)
|
||
.trim()
|
||
.toLowerCase();
|
||
const isNmcCurrent = currentSource === "nmc" || currentSource.includes("nmc");
|
||
const rawValue = firstNonEmptyString([
|
||
isNmcCurrent ? "" : detail.current?.obs_time,
|
||
localObservationTimeCandidate(detail.airport_primary?.obs_time),
|
||
localObservationTimeCandidate(detail.airport_current?.obs_time),
|
||
localObservationTimeCandidate(mgmFirstRecord?.obs_time),
|
||
localObservationTimeCandidate(mgmFirstRecord?.time),
|
||
detail.airport_primary?.report_time,
|
||
detail.airport_current?.report_time,
|
||
isNmcCurrent ? "" : detail.current?.report_time,
|
||
mgmFirstRecord?.report_time,
|
||
detail.updated_at,
|
||
]);
|
||
|
||
return (
|
||
formatObservationUpdate(rawValue, locale) ||
|
||
(isEnglish(locale) ? "Unavailable" : "未提供")
|
||
);
|
||
}
|
||
|
||
export function getCityProfileStats(detail: CityDetail, locale: Locale = "zh-CN") {
|
||
const risk = detail.risk || {};
|
||
const nearbyCount = Array.isArray(detail.mgm_nearby) ? detail.mgm_nearby.length : 0;
|
||
const nearbySource = String(detail.nearby_source || "").trim().toLowerCase();
|
||
const sourceCode = getObservationSourceCode(detail);
|
||
const isOfficialSource =
|
||
sourceCode === "hko" ||
|
||
sourceCode === "cwa" ||
|
||
sourceCode === "noaa";
|
||
|
||
const sourceDisplay = (() => {
|
||
if (sourceCode === "hko") {
|
||
return isEnglish(locale)
|
||
? "Hong Kong Observatory (HKO)"
|
||
: "香港天文台 (HKO)";
|
||
}
|
||
if (sourceCode === "cwa") {
|
||
return isEnglish(locale)
|
||
? "Central Weather Administration (CWA)"
|
||
: "交通部中央气象署 (CWA)";
|
||
}
|
||
if (sourceCode === "noaa") {
|
||
const noaaCode = getNoaaStationCode(detail);
|
||
const noaaName = getNoaaStationName(detail);
|
||
return isEnglish(locale)
|
||
? `${noaaName}${noaaCode ? ` (${noaaCode})` : ""}`
|
||
: `${noaaName}${noaaCode ? `（${noaaCode}）` : ""}`;
|
||
}
|
||
if (sourceCode === "wunderground") {
|
||
const icao = String(detail.risk?.icao || detail.current?.station_code || "")
|
||
.trim()
|
||
.toUpperCase();
|
||
const stationName = String(
|
||
detail.current?.station_name || detail.risk?.airport || "",
|
||
).trim();
|
||
return `${stationName || icao || "Airport"}${icao ? ` (${icao} METAR)` : " METAR"}`;
|
||
}
|
||
const stationName = String(
|
||
detail.current?.station_name || detail.risk?.airport || "",
|
||
).trim();
|
||
const stationCode = String(
|
||
detail.current?.station_code || detail.risk?.icao || "",
|
||
).trim();
|
||
if (stationName) {
|
||
return `${stationName}${stationCode ? ` (${stationCode})` : ""}`;
|
||
}
|
||
const tag = getObservationSourceTag(detail);
|
||
if (sourceCode === "mgm") {
|
||
return isEnglish(locale) ? `MGM (${tag})` : `MGM (${tag})`;
|
||
}
|
||
if (risk.airport && risk.icao) return `${risk.airport} (${risk.icao})`;
|
||
if (risk.airport) return String(risk.airport);
|
||
return isEnglish(locale) ? "No profile" : "暂无档案";
|
||
})();
|
||
|
||
const rows = [
|
||
{
|
||
label: isOfficialSource
|
||
? isEnglish(locale)
|
||
? "Settlement station"
|
||
: "结算站点"
|
||
: isEnglish(locale)
|
||
? "Settlement airport"
|
||
: "结算机场",
|
||
value: sourceDisplay,
|
||
},
|
||
{
|
||
label: isOfficialSource
|
||
? isEnglish(locale)
|
||
? "Reference distance"
|
||
: "参考距离"
|
||
: isEnglish(locale)
|
||
? "Station distance"
|
||
: "站点距离",
|
||
value:
|
||
risk.distance_km != null && Number.isFinite(Number(risk.distance_km))
|
||
? `${risk.distance_km} km`
|
||
: isEnglish(locale)
|
||
? "Not marked"
|
||
: "未标注",
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Observed temp" : "实测温度",
|
||
value: getObservedTemperatureProfile(detail, locale),
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Observation update" : "观测更新",
|
||
value: getObservationUpdateProfile(detail, locale),
|
||
},
|
||
{
|
||
label: isEnglish(locale) ? "Nearby stations" : "周边站点",
|
||
value:
|
||
nearbyCount > 0
|
||
? isEnglish(locale)
|
||
? `${nearbyCount} participating stations`
|
||
: `${nearbyCount} 个参与监控`
|
||
: isEnglish(locale)
|
||
? "No nearby stations"
|
||
: "暂无周边站",
|
||
},
|
||
];
|
||
|
||
if (nearbyCount > 0) {
|
||
rows.push({
|
||
label: isEnglish(locale) ? "Nearby source" : "周边站来源",
|
||
value:
|
||
nearbySource === "kma"
|
||
? isEnglish(locale)
|
||
? "KMA official stations"
|
||
: "KMA 官方站"
|
||
: nearbySource === "official_cluster"
|
||
? isEnglish(locale)
|
||
? "Official station cluster"
|
||
: "官方站簇"
|
||
: nearbySource === "mgm"
|
||
? "MGM"
|
||
: isEnglish(locale)
|
||
? "Airport / METAR network"
|
||
: "机场 / METAR 网络",
|
||
});
|
||
}
|
||
|
||
if (nearbySource === "kma" && detail.airport_current?.temp != null) {
|
||
const airportLabel =
|
||
String(
|
||
detail.airport_current.station_label ||
|
||
detail.airport_current.station_code ||
|
||
detail.risk?.airport ||
|
||
"",
|
||
).trim() ||
|
||
(isEnglish(locale) ? "Airport station" : "机场主站");
|
||
const airportObsTime =
|
||
String(detail.airport_current.obs_time || "").trim() ||
|
||
(isEnglish(locale) ? "pending" : "待更新");
|
||
const airportHigh =
|
||
detail.airport_current.max_so_far != null
|
||
? `${detail.airport_current.max_so_far}${detail.temp_symbol || ""}${
|
||
detail.airport_current.max_temp_time
|
||
? ` @ ${detail.airport_current.max_temp_time}`
|
||
: ""
|
||
}`
|
||
: isEnglish(locale)
|
||
? "Unavailable"
|
||
: "未提供";
|
||
|
||
rows.push({
|
||
label: isEnglish(locale) ? "Airport reference" : "机场主站参考",
|
||
value: `${airportLabel}: ${detail.airport_current.temp}${
|
||
detail.temp_symbol || ""
|
||
} @ ${airportObsTime}`,
|
||
});
|
||
rows.push({
|
||
label: isEnglish(locale) ? "Airport high" : "机场目前最高温",
|
||
value: airportHigh,
|
||
});
|
||
}
|
||
|
||
return rows;
|
||
}
|
||
|
||
export function getSettlementRiskNarrative(
|
||
detail: CityDetail,
|
||
locale: Locale = "zh-CN",
|
||
) {
|
||
const risk = detail.risk || {};
|
||
const sourceCode = getObservationSourceCode(detail);
|
||
const stationTerm =
|
||
sourceCode === "hko" ||
|
||
sourceCode === "cwa" ||
|
||
sourceCode === "noaa"
|
||
? isEnglish(locale)
|
||
? "settlement reference station"
|
||
: "结算参考站"
|
||
: isEnglish(locale)
|
||
? "settlement airport"
|
||
: "结算机场";
|
||
const lines: string[] = [];
|
||
|
||
if (risk.warning) {
|
||
lines.push(
|
||
isEnglish(locale)
|
||
? `Current key risk: ${risk.warning}`
|
||
: `当前主要风险是：${risk.warning}`,
|
||
);
|
||
}
|
||
|
||
if (risk.distance_km != null) {
|
||
if (risk.distance_km >= 60) {
|
||
lines.push(
|
||
isEnglish(locale)
|
||
? `The ${stationTerm} is far from urban core; market feel and settlement value may diverge significantly.`
|
||
: `${stationTerm}与城市核心区域距离偏大，盘面温度与结算值可能出现明显背离。`,
|
||
);
|
||
} else if (risk.distance_km >= 25) {
|
||
lines.push(
|
||
isEnglish(locale)
|
||
? `The ${stationTerm} has material distance from downtown; peak/overnight rhythm should prioritize the settlement station.`
|
||
: `${stationTerm}与城区存在可感知距离，午后峰值和夜间降温节奏需要优先看结算站。`,
|
||
);
|
||
} else {
|
||
lines.push(
|
||
isEnglish(locale)
|
||
? `The ${stationTerm} is close enough; city feel and settlement temperature are usually more synchronized.`
|
||
: `${stationTerm}距离较近，城市体感与结算温度通常更同步。`,
|
||
);
|
||
}
|
||
}
|
||
|
||
if (isTurkishMgmCity(detail)) {
|
||
lines.push(
|
||
isEnglish(locale)
|
||
? "For Turkish MGM-supported cities, focus on the airport station plus MGM nearby-station linkage, not urban sensation alone."
|
||
: "对接入 MGM 的土耳其城市，需要重点看机场站与 MGM 周边站联动，不能只看城区体感。",
|
||
);
|
||
}
|
||
|
||
if (detail.current?.obs_age_min != null) {
|
||
if (detail.current.obs_age_min >= 45) {
|
||
lines.push(
|
||
isEnglish(locale)
|
||
? `Current METAR is ${detail.current.obs_age_min} minutes old. Blend nearby stations for nowcast instead of single-station snapshot.`
|
||
: `当前 METAR 已有 ${detail.current.obs_age_min} 分钟时滞，临近判断要结合周边站而不是只看主站快照。`,
|
||
);
|
||
} else {
|
||
lines.push(
|
||
isEnglish(locale)
|
||
? "Primary station observation is fresh enough; short-term judgement can anchor on it."
|
||
: "当前主站观测较新，短时判断可以把主站温度作为主要锚点。",
|
||
);
|
||
}
|
||
}
|
||
|
||
return lines;
|
||
}
|
||
|
||
export function getClimateDrivers(detail: CityDetail, locale: Locale = "zh-CN") {
|
||
const drivers: Array<{ label: string; text: string }> = [];
|
||
const lat = Math.abs(Number(detail.lat));
|
||
const nearbyCount = Array.isArray(detail.mgm_nearby)
|
||
? detail.mgm_nearby.length
|
||
: 0;
|
||
const distanceKm = Number(detail.risk?.distance_km);
|
||
|
||
if (lat >= 50) {
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "High-latitude cold air" : "高纬冷空气",
|
||
text: isEnglish(locale)
|
||
? "At higher latitude, temperature rhythm is more affected by cold-air surges, trough passage, and seasonal radiation angle."
|
||
: "该城市位于较高纬度，温度变化更容易受到冷空气南下、短波槽和日照角度变化影响。",
|
||
});
|
||
} else if (lat >= 35) {
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "Mid-latitude westerlies" : "中纬西风带",
|
||
text: isEnglish(locale)
|
||
? "Temperature shifts are often controlled by frontal transitions rather than pure daytime radiation."
|
||
: "该城市主要受中纬西风带和锋面活动控制，升降温常来自气团切换，而不是单一日照变化。",
|
||
});
|
||
} else if (lat >= 20) {
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "Subtropical highs" : "副热带高压",
|
||
text: isEnglish(locale)
|
||
? "Subtropical ridge, clear-sky radiation and low-level warm advection often dominate warming efficiency."
|
||
: "该城市更容易受副热带高压、晴空辐射和低层暖平流影响，午后增温能力通常更强。",
|
||
});
|
||
} else {
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "Tropical moisture & convection" : "热带水汽与对流",
|
||
text: isEnglish(locale)
|
||
? "Temperature and feels-like are often modulated by moisture transport, cloud convection and showers."
|
||
: "该城市偏热带环境，温度与体感常受水汽输送、云对流和阵雨触发影响。",
|
||
});
|
||
}
|
||
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "Dry-wet boundary layer" : "干湿边界层",
|
||
text: isEnglish(locale)
|
||
? "Boundary-layer humidity controls daytime warming efficiency; dry boundary warms faster, wet boundary is more cloud/precip-sensitive."
|
||
: "低层干湿状态会决定午后升温效率。干空气通常升温更快，湿空气更容易受云量和降水过程抑制。",
|
||
});
|
||
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "Advection transport" : "平流输送",
|
||
text: isEnglish(locale)
|
||
? "Short-term trend is usually driven by low-level air-mass transport. Persistent wind origin tends to sustain thermal direction."
|
||
: "短时趋势常由低层气团输送控制。若风向持续来自同一侧，温度通常更容易沿该方向延续。",
|
||
});
|
||
|
||
if (Number.isFinite(distanceKm) && distanceKm >= 25) {
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "Station representativeness" : "站点代表性",
|
||
text: isEnglish(locale)
|
||
? "When settlement station is not near city core, perceived temperature and settlement value may diverge."
|
||
: "结算站与城市核心区存在一定距离时，体感温度和结算温度可能分离，评估时应优先以结算站观测为准。",
|
||
});
|
||
}
|
||
|
||
if (nearbyCount >= 4) {
|
||
drivers.push({
|
||
label: isEnglish(locale) ? "Local heterogeneity" : "局地差异",
|
||
text: isEnglish(locale)
|
||
? "More nearby stations suggest terrain/urban-heat heterogeneity; settlement station and downtown sensation should be evaluated separately."
|
||
: "周边可用站点较多，说明地形、城区热岛或下垫面差异可能明显，结算站与城区体感需要分开评估。",
|
||
});
|
||
}
|
||
|
||
return drivers;
|
||
}
|