Paired Satellite and NWP Precipitation for Global Flood Forecasting


Huang Z., Wu H., Gu G., Li X., Nanding N., Adler R. F., ...Daha Fazla

Journal of Hydrometeorology, cilt.24, sa.12, ss.2191-2205, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 24 Sayı: 12
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1175/jhm-d-23-0044.1
  • Dergi Adı: Journal of Hydrometeorology
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aqualine, Aquatic Science & Fisheries Abstracts (ASFA), Artic & Antarctic Regions, CAB Abstracts, Environment Index, Geobase, Pollution Abstracts, Veterinary Science Database
  • Sayfa Sayıları: ss.2191-2205
  • Anahtar Kelimeler: Error analysis, Forecast verification/skill, Numerical analysis/modeling, Operational forecasting
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Precipitation data are known to be the key driver of hydrological simulations. Hence, reliable quantitative precipitation estimates and forecasts are vital for accurate hydrological forecasting. Satellite-based precipitation estimates from Integrated Multi-satellitE Retrievals for GPM Early Run (IMERG-E) and forecasted precipitation from NASA’s Goddard Earth Observing System Forward Processing (GEOS-FP) have shown values in global flood nowcasting and forecasting. However, few studies have comprehensively evaluated their hydrological performance let alone explored the potential value of combining them. Therefore, this study undertakes a quasi-global evaluation of their utility in real-time hydrological monitoring and 1–5-day forecasting with the Dominant River Tracing-Routing Integrated with Variable Infil-tration Capacity (VIC) Environment (DRIVE) model. The gauge-corrected IMERG Final Run precipitation estimates and corresponding hydrological simulation are used as the references. Results showed that the hit bias is the dominant error source of IMERG-E, while the false precipitation is more noticeable in GEOS-FP. In terms of hydrological perfor-mance, the GEOS-FP-driven model (DRIVE-FP) performance is close to the IMERG-E-driven model (DRIVE-E) performance on day 1, indicating that GEOS-FP could nicely fill the gap of nowcasting caused by the IMERG-E time la-tency. For longer lead-time forecasts, the bias tends to diminish in most regions, likely because the under-or overestima-tion in IMERG-E is generally offset by the distinct types of misestimation in GEOS-FP. The skillful initial hydrological conditions present outperformed forecasts in most regions, except for tropical areas where the accuracy of GEOS-FP prevails. Overall, this study provides a valuable view of the combined use of IMERG-E and GEOS-FP precipitation in the context of hydrological nowcasts and forecasts.