02.08.2018 - UNESCO Office in Nairobi

An iRain App for Eastern African Countries

Participants and organizers of the Regional Training Workshop on Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network, in Uganda, from 23-25 July 2018 (c)UNESCO

UNESCO Regional Office for Eastern Africa, under the International Hydrology Programme, jointly with Department of Geography, Geo-informatics and Climate Sciences of Makerere University, organized a Regional Training Workshop on Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network, in Uganda, from 23-25 July 2018

In the last decade, different satellite precipitation products have become widely available. These products, some of which are global and available in near-real time, integrate different estimates of precipitation from different sensors and satellites into a homogeneous format product, with a specific grid cell resolution and temporal aggregation.

The use of these products in hydrologic applications has opened new venues to support water management globally. In poorly gauged basins and large basins with larger concentration times, satellite precipitation products may be the only input data timely enough to allow flow predictions downstream with enough lead time to implement management and response actions based on such predictions.

The UNESCO-International Hydrological Programme (UNESCO-IHP)<a name="siteName"></a> under the Global Network on Water and Development Information for Arid Lands (G-WADI network), is working closely with the Center for Hydrometeorology & Remote Sensing (CHRS) at the University of California, Irvine (UCI) in developing the PERSIANN System (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks).

Since its early inception in 1997, PERSIANN has been a continuously evolving system, including the creation of two more PERSIANN systems, PERSIANN-CCS (Cloud Classification System) and PERSIANN-CDR (Climate Data Record). From the PERSIANN-CCS system, the iRain application was created, which allows users to visualize real-time global satellite precipitation observations and track extreme precipitation events globally.

iRain provides access to real-time global high-resolution (~4km) satellite precipitation products from the PERSIANN-CCS system. The building block of iRain rests on the satellite precipitation estimates generated by the PERSIANN algorithm which has been under development for over two decades.

The training workshop, supported by Center for Hydro-meteorology and Remote Sensing, University of California (Irvine) and international Center for Integrated Water Resources Management (ICIWaRM) under the Auspicious of UNESCO, saw the presence of 30 participants from 11 countries representing the Intergovernmental Authority on Development (IGAD), the East African Community (EAC), the Intergovernmental Oceanographic Commission (IOC), and Regional Economic Commissions Member Countries. The experts gathered to learn to make real time rainfall measurement for their country and come out with proper flood warning measures.

“Climate data is not readily accessible in many countries, and, as a scientist and educator, this is a major obstacle which affects my research and training”- Associate Professor Manta Devi Nowbuth, from the Faculty of Engineering at the University of Mauritius shared. “Through this training we got the opportunity to learn and use the CHRS Rain Sphere/IRain and Data Portal System and helped me better operate and appreciate the iRain System. The system enables rapid and easy access to rainfall data spatially at global level and up to hourly level, presenting a sound working tool for many scientists. I am thankful for the organisers of the workshop, as well as those who contributed to the development of the Data Portal” he concluded.

The iRain mobile app is a complement to the iRain web application athttp://irain.eng.uci.edu/. The mobile app allows users to not only visualize real-time global satellite precipitation observations and track extreme precipitation events globally, but also report their local rainfall information to supplement our data by using the crowdsourcing functionality of the app. A useful feature of iRain is real-time rainfall observation data, which can easily be shared through social networks, i.e. Facebook, Twitter. In addition, rainfall events can be viewed as an animation to observe their change over time, as an accumulation of rain or as a time lapse. Precise measurement of rainfall at a given point can be observed by zooming in to the app.

Eastern Africa is a region facing multiple challenges when it comes to flood and drought management. Building capacity at regional level to reduce effects of disasters is fundamental for sustainable development. Until now, insufficient attention has been put on developing technical capacity across the region for improved knowledge in the use of remote sensing technologies for rain fall estimation.

The training specifically focused on technical personnel from meteorological/hydrological services as well as scientist from training and research institutions. The technical personnel from meteorological services, another one worked with university / research institution experts jointly to analyse the data from their country. The experts were introduced to the theoretical background, followed by methodology to use the various operation in the iRain system on how to extract the rainfall information. A series of case studies using rainfall data and PERSIANN-CCS systems were carried out, along with a short-session with students of Makerere University on using the iRain app function took place.

Ensuring knowledge at the technical level is communicated upwards to decision makers and horizontally across sectors is essential for main-streaming for any hydrological extreme event, and so any technical activity should go hand-in-hand with institutional capacity development at the policy level.

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