Ensemble forecast interpretation
Ensemble weather and flood forecasts are summarised as probabilities of exceeding thresholds, so users see the chance of a hazard rather than a single scenario.
GCRI · Iklim dan Bahaya
Forecasting and time-series analysis supply the predictive side of hazard evidence: weather and flood forecasts, seasonal outlooks and statistical predictions. In this field the emphasis is on probabilistic forecasts and on verifying them honestly against what happened.
Forecasting and time-series analysis predict future values of variables from past observations and explanatory information. They support peringatan dini and planning across hazards, markets and health. In climate and hazards and disaster and crisis, forecasts trigger early action and anticipatory finance before shocks materialise. Probabilistic forecasts allow decisions to account for uncertainty across connected sistem. The canonical description is on STEM Commons.
Ensemble weather and flood forecasts are summarised as probabilities of exceeding thresholds, so users see the chance of a hazard rather than a single scenario.
Seasonal forecasts from several centres are combined, and their skill for the region and season is shown beside every outlook so users know when to trust it.
Forecasts are scored against observations with proper scoring rules and compared with reference forecasts such as climatology.
Rain, daytime surface heat and flood water across the world, from NASA GIBS. Each layer carries its own date.
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Lapisan 3
Sinyal iklim, untuk halaman ini
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Terbaru yang tersedia
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © kontributor OpenStreetMap (ODbL) · Natural Earth
Memuat citra NASA terbaru.
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Sinyal iklim, dibingkai pada dunia.Produk satelit dan model sebagaimana diterbitkan NASA, masing-masing dengan tanggalnya sendiri. Produk ini adalah indikator, bukan penilaian atas tempat mana pun.
Lapisan dan tanggal
Datasets and records used by forecasting and time-series analysis on this platform, with the role each plays and the label its values carry. Sources are listed in register sumber.
| Data | Peran | Label |
|---|---|---|
| ECMWF and other centres’ ensemble forecasts | Probabilistic predictions | PRAKIRAAN |
| Copernicus C3S multi-system seasonal forecasts | Seasonal outlooks | PRAKIRAAN |
| Station and gauge observations | Verifikasi | TERAMATI |
| Reforecast archives | Skill estimation | DIMODELKAN |
Disusun dari profil bidang Nexus Standards profil area Standar risiko iklim: bahaya yang disebutkannya, sistem dan sektor yang menanggung kerugian, kendali yang meredamnya, dan data yang mengamatinya. Pilih komponen, tentukan bahaya pemicu, dan telusuri kaskade langkah demi langkah. Tampilan Peta menempatkan proses pada contoh geografi dengan data terbuka. Setiap bobot keterkaitan adalah asumsi yang dinyatakan dan dapat Anda ubah. Model pengajaran, bukan prakiraan, penilaian, atau sertifikasi. Untuk memodelkan tempat pilihan Anda sendiri, buka System Builder.
Bahaya
Sistem dan keterkaitan
Kendali
NS-0 Anggaran dasar dan prinsipNS-1 Observatory UNI dan katalog artefak (tata bahasa v0.2: segmen domain, sektor, wilayah, dan lingkungan)NS-3 UNI catatan risiko (tata bahasa, pemetaan ke sistem lama, kewenangan alokasi)NS-3b Profil metadata dataset dan produk (STAC, DCAT, PROV-O)NS-9 UNI kontekstual (penerapan, instans, instans program)NS-11 Verifikasi dan pemantauan (bukti, atestasi, pengamatan kesesuaian zero trust)NS-14 Kesesuaian dan pemetaan silang ke standar eksternalNRS-H65 Keluarga bahaya: Pelampauan batas planet (NHS-1 planet.boundary)NRS-H62 Keluarga bahaya: Peristiwa majemuk dan multibahaya (NHS-1 sys.compound)NRS-H71 Keluarga bahaya: Bencana zaman purba dan kosmik (NHS-1 planet.deep-time)NRS-H79 Keluarga bahaya: Krisis kesehatan jiwa (NHS-1 health.mental)NRS-H75 Keluarga bahaya: Penyakit yang peka iklim (NHS-1 health.climate-sensitive)NRS-H7 Keluarga bahaya: Anomali sirkulasi skala besar (NHS-1 atmo.climate-mode)Pengamatan
Contoh geografi
Forecasts are evaluated out of sample with proper scoring rules and reliability diagrams. Rolling-origin evaluation tests performance over time.
| Pemeriksaan | Cara pelaksanaannya |
|---|---|
| Proper scoring rules | Forecasts are scored with measures such as the continuous ranked probability score that reward honest probabilities |
| Reliability diagrams | Forecast probabilities are compared with observed frequencies |
| Reference comparison | Skill is always stated against a reference such as climatology or persistence |
Structural breaks and regime changes undermine models trained on the past. Forecast skill typically declines rapidly with lead time.
Model, asumsi, data, dan ketidakpastiannya, dalam bentuk yang akan diperiksa ilmuwan atau insinyur. Strukturnya mengikuti metode yang dipublikasikan. Nilai yang digambar bersifat ilustratif, bukan temuan.
How far the outlook for forecasting for hazards could spread, shown as ranges rather than a single line.
Process explorer · Process
9 steps·3 stages·1 gate
Proses
The WMO flood forecasting manual and Early Warnings for All describe the chain from forecast to action, across EW4All’s four pillars.
Neutral outline of a published external standard or method, from its issuing body. Not a record of operation. Nexus does not perform, certify or approve any step shown. A gate or decision belongs to the party the source names.
Climate and Hazards stewards forecasting and time-series analysis for the Consortium and reviews how it is applied across platforms.
Laporan is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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