INVESTIGADORES
DILLON Maria Eugenia
artículos
Título:
Hydrometeorological observations and modeling of an extreme rainfall event using wrf and wrf-hydro during the relampago field campaign in Argentina
Autor/es:
PAL, SUJAN; DOMINGUEZ, FRANCINA; DILLON, MARÍA EUGENIA; ALVAREZ, JAVIER; GARCIA, CARLOS MARCELO; NESBITT, STEPHEN W.; GOCHIS, DAVID
Revista:
JOURNAL OF HYDROMETEOROLOGY
Editorial:
AMER METEOROLOGICAL SOC
Referencias:
Año: 2021 vol. 22 p. 331 - 351
ISSN:
1525-755X
Resumen:
Some of the most intense convective storms on Earth initiate near the Sierras de Córdoba mountain range in Argentina. The goal of the RELAMPAGO field campaign was to observe these intense convective storms and their associated impacts. The intense observation period (IOP) occurred during November?December 2018. The two goals of the hydrometeorological component of RELAMPAGO IOP were 1) to perform hydrological streamflow and meteorological observations in previously ungauged basins and 2) to build a hydrometeorological modeling system for hindcast and forecast applications. During the IOP, our team was able to construct the stage?discharge curves in three basins, as hydrological instrumentation and personnel were successfully deployed based on RELAMPAGO weather forecasts. We found that the flood response time in these river locations is typically between 5 and 6 h from the peak of the rain event. The satellite-observed rainfall product IMERG-Final showed a better representation of rain gauge?estimated precipitation, while IMERG-Early and IMERG-Late had significant positive bias. The modeling component focuses on the 48-h simulation of an extreme hydrometeorological event that occurred on 27 November 2018. Using the Weather Research and Forecasting (WRF) atmospheric model and its hydrologic component WRF-Hydro as an uncoupled hydrologic model, we developed a system for hindcast, deterministic forecast, and a 60-member ensemble forecast initialized with regional-scale atmospheric data assimilation. Critically, our results highlight that streamflow simulations using the ensemble forecasting with data assimilation provide realistic flash flood forecast in terms of timing and magnitude of the peak. Our findings from this work are being used by the water managers in the region.