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Welcome

· One min read
Prakrut Kansara
Research Scientist @JHU
Qibo Kris Su
Undergrad Student @JHU

Welcome to our new documentation site! This site is powered by Docusaurus which is a website generator built by Meta's open source team using React frame work.

You hear us right, it is a website generator... Most of our pages are prepared in Markdown format and hosted in a GitHub Repo.

In the near future, this website will be used as the hub of presenting the geoprocessing and statistical methods we used when building our webapp.

Stay tuned!

Evolution & Development of Amazon HydroViewer

· One min read
Qibo Kris Su
Undergrad Student @JHU

This blog post documents the development of our web app.

May 22nd, 2024 (Version 0.0.1)

The first demo we did through arcgis experience builder, the data are processed with Hydrobasins at level 2. This prototype serves as our proof of concept, it has most fundamental elements a map based dashboard would have.

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May 30th, 2024 (Version 0.0.2)

UI got it redesign for the first time

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July 2nd, 2024 (Version 0.0.2.1)

The interface underwent another redesign, and is currently kept to look as the following. We currently only made hosting our retrospective measurements and their anomaly values in this

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July 18th, 2024 New Prototype Using Plotly

A new prototype is being built using Plotly Dash and their bootstrap components.

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Managing fire risk in the Amazon ahead of an El Nino year

· One min read
Prakrut Kansara
Research Scientist @JHU

The Amazon Rainforest, commonly known as the "lungs of the Earth," is crucial for regulating the global climate and preserving biodiversity. However, it is under threat from deforestation and an increasing number of wildfires due to long-term climate change and short-term climate variability. One major factor that heightens the fire risk in the Amazon is the El Niño phenomenon, which typically worsens dry conditions. SERVIR, a partnership between NASA and USAID, provides specialized forecasts (ranging from subseasonal to seasonal) that are essential for predicting and mitigating these risks.

Global climate models have demonstrated the ability to accurately predict the development of El Niño. Their subseasonal to seasonal (S2S) forecasts deliver vital information on weather and climate patterns over periods ranging from a few weeks to several months. In the Amazon, these forecasts provide a critical opportunity to prepare for the heightened fire risk linked to El Niño events. With advanced knowledge of when and where dry conditions are expected, authorities and organizations can implement proactive strategies to minimize the impact of wildfires.

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For those of you interested read the full release HERE