Gonzalo Peña-Castellanos [he/him]

Bogota, D.C., Capital District, Colombia Contact Info
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About

JupyterLab and napari core developer, working on localization, internationalization…

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Experience & Education

  • Python Software Foundation

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Publications

  • Allowing citizens to effortlessly become rainfall sensors

    36th IAHR World Congress. The Hague, the Netherlands

    Lack of data is one of the most common problems in water management. Although technologies to produce data with enough spatial and temporal resolution and acceptable quality and quantity are available, they are only affordable by a few countries in the world. In parallel, we are experiencing an exciting technological moment. There will soon be one smart-phone for every five people in the world and there are already more mobile phones subscriptions in use than humans alive. These developments…

    Lack of data is one of the most common problems in water management. Although technologies to produce data with enough spatial and temporal resolution and acceptable quality and quantity are available, they are only affordable by a few countries in the world. In parallel, we are experiencing an exciting technological moment. There will soon be one smart-phone for every five people in the world and there are already more mobile phones subscriptions in use than humans alive. These developments make the concept of citizen observatories interesting to collect denser information in space and time, and to promote the participation of the public in a variety of different ways. We present the results of diverse experiments that aim to facilitate citizens using smart-phones. In the context of the WeSenseIt project, the use of arbitrary scales, textual descriptions, pictures and videos are explored, being the latter an interesting option that is effortless to a common citizen and might provide potentially acceptable information for scientific purposes.

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  • Evaluating the impact of climate change on urban scale extreme rainfall events: Coupling of multiple global circulation models with a stochastic rainfall generator

    9th International Conference on Urban Drainage Modelling Belgrade

    Assessing the impact of climate change in an urban drainage context requires the use of tools and methodologies that work at the local scale and fine temporal resolution. This paper aims to provide a methodology for the downscaling of an ensemble of Global Circulation Models (GCMs) output in order to produce synthetic point urban scale rainfall series using an hourly stochastic rainfall generator. In order to combine the results of several GCMs, a previously developed methodology makes use of…

    Assessing the impact of climate change in an urban drainage context requires the use of tools and methodologies that work at the local scale and fine temporal resolution. This paper aims to provide a methodology for the downscaling of an ensemble of Global Circulation Models (GCMs) output in order to produce synthetic point urban scale rainfall series using an hourly stochastic rainfall generator. In order to combine the results of several GCMs, a previously developed methodology makes use of Bayesian approach to produce a probabilistic distribution of the factors of change for different statistical properties. These factors will be applied to the statistical properties of the observed data in order to re-evaluate the parameters of the rainfall generator. Hourly rainfall data from the city of Kochi (Japan) for the period of 1976-2000 has been used to assess the proposed methodology. The stochastic downscaling process makes use of twelve GCMs as input for the periods of 2046-2065 and 2081-2100 and scenarios A1b, B1 and A2 as adopted by the intergovernmental panel on climate change (IPCC). Results are derived from multiple future realizations of climate for the different scenarios and periods.

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Languages

  • Spanish

    Native or bilingual proficiency

  • English

    Full professional proficiency

  • French

    Professional working proficiency

  • Portugués

    Elementary proficiency

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