A workshop shows early signs of climate scientists and data scientists coming together.
Climate cycles, machine learning and improved models were all part of the discussions at the first New York Academy of Sciences Workshop on Climate Informatics.
The need for temperature, wind, and solar analytics will likely increase.
The increase of large-scale infrastructure investments in the alternative energy sector will likely be accompanied by demand for data-driven services that can optimize efficiency of the related operational costs.
Financial stability can benefit from approaches grounded in the natural sciences.
Large-scale events that have disrupted supply chains underscore the importance of viewing the world through a spatial lens.
How can massive environmental datastreams create new markets?
Because companies are tracking their inputs and byproducts carefully, there has been an exponential increase in the amout of efficiency/environmental data available for primary stakeholders and investors.
The connection between the La Nina phenomenon and food prices.
In the weather and climate community, 2010 will be remembered as a year where the strong La Nina pattern exerted a significant influence on global agricultural production.
A potential India-U.S. partnership could lead to better forecasting through collaboration.
A potential new partnership between U.S. agencies and the Indian Meteorological Department could could open up an "ensemble approach" to forecasting that encourages collaboration and breaks down proprietary barriers.
There's considerable promise in data sources targeting the global agricultural community.
High-quality and high-margin products will come to market that have their roots in agricultural data acquisition and repackaging.
How satellites and sensors can assess the health of crops.
Many satellites capture everything from ocean temperatures, to land reflectance at the surface of the Earth, to global chlorophyll production. Here's a look at how that data can reveal the condition of a country's crops.
The predictive power of weather info, as illustrated by cows and La Niña.
A forecast — weather or otherwise — is always a blend of art and science. Nothing is foolproof. But in this post, Michael Ferrari shows how simple analysis can reveal a connection between a weather event (La Niña) and commodity production (milk).
Data and low-cost sensor networks can spot extreme weather before it hits.
Identifying extreme weather patterns can minimize impact when that weather arrives. But to improve long-range forecasts, we'll need to create environmental sensor networks out of phones, satellites and other technology.