R2: Downsides and Potential Pitfalls for ESS ML Prediction

Datasaurus plot
Always plot your data!

Regression analysis is a fundamental concept in the field of machine learning (ML), in that it helps establish relationships among the variables by estimating how one variable affects the other.

The coefficient of determination, R2 (pronounced “R squared”), is a measure that provides information about how well the regression line suggested by a numerical model approximates the actual data (often referred to as “goodness of fit”).

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Self Organizing Maps for Earth Systems Science

Representation of Self Organizing Map
Representation of nodes in a Self Organizing Map.

A self-organizing map (SOM), sometimes known as a Kohonen map after its originator the Finnish professor Teuvo Kohonen, is an unsupervised machine learning technique used to produce a low-dimensional representation of a higher dimensional data set. SOMs are a specific type of artificial neural network, but use a different training strategy compared to more traditional artificial neural networks (ANNs). SOMs can be used for clustering, dimensionality reduction, feature extraction, and classification — all of which suggest that they can be important tools for understanding large Earth Systems Science (ESS) datasets.

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NSF Seeks Input on Public Access Plan

NSF logo

The National Science Foundation (NSF) is seeking public input from the science and engineering research and education community on implementing the NSF Public Access Plan 2.0.

The Public Access Plan 2.0 is an update to NSF current public access requirements in response to recent White House Office of Science and Technology Policy guidance; among other things, it addresses potential equity impacts of public access requirements.

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Radio Occultation Data from COSMIC Available in the IDD

COSMIC logo

The Unidata Program Center is partnering with UCAR's COSMIC program to provide radio occultation data provided by Spire Global. The products described below are now available via the Internet Data Distribution (IDD) network. Data are on the EXP feed with a typical total volume of 80-110 MB per hour.

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Unidata to Mint NFTs of Popular Storms

Hurricane Katrina NFT

Everyone loves to talk about the weather. But until now, serious collectors of weather memorabilia have been left on the sidelines. Oh, a lucky few manage to save enormous hailstones in their freezers, but most are limited to screen shots of satellite or radar imagery, or maybe articles clipped from the local newspaper.

But never fear: Unidata is preparing to bring weather collectibles into the twenty-first century by minting a series of Non Fungible Tokens (NFTs) based on significant weather events. Our inaugural series will consist of 902 distinct NFTs of Hurricane Katrina, one for each millibar of the storm's lowest recorded atmospheric pressure.

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News and information from the Unidata Program Center
News@Unidata
News and information from the Unidata Program Center

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