Meteorology & Climate Sciences

Cal Adapt: An engrossing one-stop shop for California's climate future goes online.

Cal-Adapt has been designed to provide access to data and information that has been, and continues to be, produced by the State's scientific and research community. The data available in this site offer a view of how climate change might affect California at the local level. Here you can work with visualization tools, access data, and participate in community sharing to contribute your own knowledge.

Climate Reanalyzer is being developed by the Climate Change Institute at the University of Maine to provide an intuitive platform for visualizing a variety of weather and climate datasets and models. Investigate climate using interfaces for reanalysis and historical station data. Plot maps, timeseries, and correlations; export timeseries data to a text file for later use in spreadsheet software; export map layers to Google Earth.

Climate indicator datasets.

NOAA Climate.gov is a source of timely and authoritative scientific data and information about climate. Our goals are to promote public understanding of climate science and climate-related events, to make our data products and services easy to access and use, to provide climate-related support to the private sector and the Nation’s economy, and to serve people making climate-related decisions with tools and resources that help them answer specific questions.

The Wildland Fire Trends Tool (WFTT) is a data visualization and analysis tool that calculates and displays wildfire trends and patterns for the western U.S. based on user-defined regions of interest, time periods, and ecosystem types. Users can use the tool to easily generate a variety of maps, graphs, and tabular data products that are informative for all levels of expertise.

Commercial weather service that provides real-time weather information via the Internet.

Mission: To provide the paleoclimate data and information needed to understand and model inter-annual to centennial-scale environmental variability