Asset Details
MbrlCatalogueTitleDetail
Do you wish to reserve the book?
Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications
by
Codo, Mayra
, Rico-Ramirez, Miguel A.
in
Earth science
/ Ensemble forecasting
/ Flood predictions
/ Flood warning systems
/ Flood warnings
/ Floods
/ flow forecast
/ Forecasting
/ Ground truth
/ Hydrology
/ Lead time
/ nowcasting
/ Precipitation
/ probabilistic forecasts
/ Propagation
/ Radar
/ radar ensembles
/ Radar rainfall
/ Radar rainfall estimation
/ Rain
/ Rain gauges
/ Rainfall
/ Rainfall estimation
/ Rainfall forecasting
/ Sewer systems
/ Statistical analysis
/ Uncertainty
/ Urban areas
/ Warning systems
/ Weather forecasting
2018
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
You are currently in the queue to collect this book. You will be notified once it is your turn to collect the book.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications
by
Codo, Mayra
, Rico-Ramirez, Miguel A.
in
Earth science
/ Ensemble forecasting
/ Flood predictions
/ Flood warning systems
/ Flood warnings
/ Floods
/ flow forecast
/ Forecasting
/ Ground truth
/ Hydrology
/ Lead time
/ nowcasting
/ Precipitation
/ probabilistic forecasts
/ Propagation
/ Radar
/ radar ensembles
/ Radar rainfall
/ Radar rainfall estimation
/ Rain
/ Rain gauges
/ Rainfall
/ Rainfall estimation
/ Rainfall forecasting
/ Sewer systems
/ Statistical analysis
/ Uncertainty
/ Urban areas
/ Warning systems
/ Weather forecasting
2018
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications
by
Codo, Mayra
, Rico-Ramirez, Miguel A.
in
Earth science
/ Ensemble forecasting
/ Flood predictions
/ Flood warning systems
/ Flood warnings
/ Floods
/ flow forecast
/ Forecasting
/ Ground truth
/ Hydrology
/ Lead time
/ nowcasting
/ Precipitation
/ probabilistic forecasts
/ Propagation
/ Radar
/ radar ensembles
/ Radar rainfall
/ Radar rainfall estimation
/ Rain
/ Rain gauges
/ Rainfall
/ Rainfall estimation
/ Rainfall forecasting
/ Sewer systems
/ Statistical analysis
/ Uncertainty
/ Urban areas
/ Warning systems
/ Weather forecasting
2018
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications
Journal Article
Ensemble Radar-Based Rainfall Forecasts for Urban Hydrological Applications
2018
Request Book From Autostore
and Choose the Collection Method
Overview
Radar rainfall forecasting is of major importance to predict flows in the sewer system to enhance early flood warning systems in urban areas. In this context, reducing radar rainfall estimation uncertainties can improve rainfall forecasts. This study utilises an ensemble generator that assesses radar rainfall uncertainties based on historical rain gauge data as ground truth. The ensemble generator is used to produce probabilistic radar rainfall forecasts (radar ensembles). The radar rainfall forecast ensembles are compared against a stochastic ensemble generator. The rainfall forecasts are used to predict sewer flows in a small urban area in the north of England using an Infoworks CS model. Uncertainties in radar rainfall forecasts are assessed using relative operating characteristic (ROC) curves, and the results showed that the radar ensembles overperform the stochastic ensemble generator in the first hour of the forecasts. The forecast predictability is however rapidly lost after 30 min lead-time. This implies that knowledge of the statistical properties of the radar rainfall errors can help to produce more meaningful radar rainfall forecast ensembles.
This website uses cookies to ensure you get the best experience on our website.