Speaker
Description
In a warming climate, the expectation is that most regions will experience an increase in extreme precipitation (10 and 50 years) events. The latest IPCC (AR6) report finds that the frequency and intensity of heavy rainfall events “have likely increased at the global scale over a majority of land regions with good observational coverage”. In regions with sparse or no in situ measurements, this presents a real challenge, especially if the area is already vulnerable to extreme events. In these cases, accurate forecasts are essential to mitigate the impacts of heavy rainfall. Additionally, these areas are often remote or lack the local infrastructure to provide the decision-makers on the ground with regular regional forecasts.
In this study, we will utilise a data assimilation framework to assess whether a state-of-the-art generative weather forecast model can provide actionable information for decision-makers. Our case study will focus on the 2022 flooding in Pakistan (June to October), which killed 1,739 people and caused $30 billion of damage and economic losses. We will investigate the impact of assimilating high-resolution total column water vapour from ESA CCI on precipitation skill for these experiments, benchmarking the forecasts against NASAs Integrated Multi-satellitE Retrievals for GPM (IMERG) product. Finally, we discuss how the ability of these models to produce ensembles can be used to provide actionable information.
| You plan to attend | On site (at FZ Jülich) |
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