Accurate prediction of sea level is arguably one of the most important societal goals facing the research community. Combining cutting-edge technologies with sustained observations to understand processes and improve numerical models will be required to address the issue of future ice-sheet changes and impacts on global sea level.
In Plenty Magazine, Samantha Cleaver reports that “as baby boomer-era school buildings become more and more outdated, many districts are building green schools to replace energy guzzling, polluted learning environments.”
Over the past five years, Jackson State University has taken a leading role in the development of a world-class mesoscale observing network in Mississippi for research, education, and operational use: The Mississippi Mesonet (White and Matlack 2005). Broadly speaking a mesonet can be considered to be a network of automated weather observing stations whose spatial distribution facilitates near-real time description in between the standard “synoptic” observing stations of the National Weather Service (NWS) and Federal Aviation Administration (FAA). In many cases, they are characterized by improved temporal resolution and supplemental sensors compared to the synoptic network.