Mawün-NRT: Near real-time gridded precipitation for Chile
My Caption
Motivation
In an era characterized by increasing climate variability and the intensification of extreme weather events, the need for accurate and timely precipitation data has never been more critical. While several websites and applications offer weather forecasts that are improving every day, there is a critical gap in readily available post-event precipitation data.
Description
Mawün-NRT (in Mapuzungun, “mawün” means “rain”) is a free and publicly accessible web platform (https://mawunNRT.cr2.cl/) that provides a user-friendly visualisation of the spatio-temporal distribution of precipitation events for continental Chile in near real-time.
Main screen of Mawün-NRT web platform
Mawün-NRT was developed by the former student Rodrigo Marinao and I with the support of the Water Resources Observatory of the Araucanía Region Kimün-Ko and the Center for Climate and Resilience Research (CR2), to supplement the existing web platform Mawün (https://mawun.cr2.cl/), which is focused on historical precipitation data.
Three state-of-the-art precipitation products are included in this first version of Mawün-NRT:
i) the near-real-time Multi-Source Weather (MSWX-NRT, 3-hourly, 0.1°),
ii) PERSIANN Dynamic Infrared–Rain Rate (PDIR-Now, hourly and 0.04°) and
iii) the Integrated Multi-satellitE Retrievals for GPM (IMERGv07 and IMERGv06, half-hourly, 0.1°) in both the Early and Late versions.
In addition, hourly data from hundreds of rain gauges of different Chilean institutions (e.g. DGA, DMC, Agromet, CEAZA) are collected in near real-time by the Vismet web platform (https://www.vismet.cr2.cl/) and used in Mawün-NRT to compare the gridded precipitation estimates with the corresponding in situ values, as a soft measure of the uncertainty in the precipitation estimates.
The near real-time capabilities of Mawün-NRT allows decision makers to evaluate which product provides better identification of the spatial area really affected by the precipitation event, fostering a timely decision-making and a proactive response to evolving weather conditions. A case study shows the monitoring of an extreme event that affected the south-central area of Chile in June of this year 2024, with devastating societal and economic impacts.
A detailed tutorial can be found here.
Some example applications can be found here.
I am an Associate Professor in the Department of Civil Engineering at the University of La Frontera. I hold a PhD in Environmental Engineering from the University of Trento (Italy) and completed postdoctoral training at the European Commission’s Joint Research Centre. I have more than 20 years of experience in water resources research and have previously served as an Associate Researcher at the Center for Climate and Resilience Research (CR)2 and as a member of the Earth Sciences Assessment Group of the Chilean National Research and Development Agency (ANID).
My research lies at the interface of hydrology, data science, and environmental sciences, with a particular focus on the use of gridded datasets and open-source tools to investigate droughts, extreme events, and water-related impacts of global change.
I work across spatial and temporal scales to improve the understanding of catchment-scale hydrological processes and to translate this knowledge into operational modelling, forecasting, and early-warning systems that support robust environmental decision-making.
Please reach out to collaborate 😃