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GloFAS-ERA5 reanalysis: River discharge ‘maps without gaps’ from 1979-present

GloFAS-ERA5 reanalysis: River discharge ‘maps without gaps’ from 1979-present

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Contributed by Shaun Harrigan, ECMWF. In an ideal world we would have river discharge measurements for every river spanning many decades and updated in real time. We all know this is very far from reality with severe gaps in the global observing network (Lavers et al., 2019), and provides a fundamental challenge for hydrological monitoring and forecasting. A way forward pioneered in the field of meteorology and climate is to optimally combine available in situ and satellite Earth system observations…

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Verification of U.S. National Hurricane Center’s forecast advisories, 2006-2019

Verification of U.S. National Hurricane Center’s forecast advisories, 2006-2019

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Below is a re-post of a blog post that I recently published at forecastverification.com, which is a small company that I operate in part-time (in addition to my hydrometeorologist job at Deltares). While hurricane forecasting is a little removed from hydrometeorology, I figured that the disciplines have sufficient overlap for this to be interesting to the HEPEX community also. Happy reading! Introduction Post Hurricane Irma’s passage over Florida, back in September 2017, I analysed the quality of the forecasts that…

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Hydrometeorological forecast verification: the detail matters!

Hydrometeorological forecast verification: the detail matters!

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Contributed by Seonaid Anderson, CEH.  Spending time and effort developing a novel hydrological ensemble prediction system, demonstrating its value, comparing with existing systems, justifying all that effort… there are many reasons why we verify our ensemble prediction systems. Before we dive into the number crunching, a few obvious questions need to be asked. What period to use for evaluation? This is often as long as possible, while maintaining relevance to the current application and subject to the usual computing constraints. What…

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Is One Forecast Model Better Than Another?

Is One Forecast Model Better Than Another?

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Blog post contributed by: Tim DelSole* The Sign Test Is one forecast model better than another? A natural approach to answering this question is to run a set of forecasts with each model and then see which set has more skill. This comparison requires a statistical test to ensure that the estimated difference represents a real difference in skill, rather than a random sampling error. Unfortunately, there are three problems with using standard difference tests: they have low statistical power,…

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Lessons from calibrating a global flood forecasting system

Lessons from calibrating a global flood forecasting system

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Contributed by Feyera Hirpa, University of Oxford. Hydrological models are key tools for predicting flood disasters several days ahead of their occurrence. However, their usability as a decision support tool depends on their skill in reproducing the observed streamflow. The forecast skill is subject to a cascade of uncertainties originating from errors in the models’ structure, parametrization, initial conditions and meteorological forcing. The Global Flood Awareness System (GloFAS) is an operational flood forecasting system that produces ensemble streamflow forecasts with…

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