Developing answers to these types of questions for locations has typically required extensive work to gather data, conduct analyses, and generate relevant explanations and graphics. Too frequently providers don't have ready access to or knowledge of reliable, trusted data sets, nor sound, scientifically accepted analysis techniques such that they can provide a rapid response to queries they receive.
In order to support National Weather Service (NWS) local office forecasters with information they need to deliver timely responses to climate-related questions from their customers, we have developed the Local Climate Analysis Tool (LCAT). LCAT uses the principles of artificial intelligence to respond to queries, in particular, through use of machine technology that responds intelligently to input from users. A user translates customer questions into primary variables and issues and LCAT pulls the most relevant data and analysis techniques to provide information back to the user, who in turn responds to their customer. Most responses take on the order of 10 seconds, which includes providing statistics, graphical displays of information, translations for users, metadata, and a summary of the user request to LCAT.
Applications in Phase I of LCAT, which is targeted for the NWS field offices, include Climate Change Impacts, Climate Variability Impacts, Drought Analysis and Impacts, Water Resources Applications, Attribution of Extreme Events, and analysis techniques such as time series analysis, trend analysis, compositing, and correlation and regression techniques. Data accessed by LCAT are homogenized historical COOP and Climate Prediction Center climate division data available at NCDC. Applications for other NOAA offices and Federal agencies are currently being investigated, such as incorporation of tidal data, fish stocks, sea surface temperature, health-related data, and analyses relevant to those datasets.
We will describe LCAT, its basic functionality, examples of analyses, and progress being made to provide the tool to a broader audience in support of ocean, fisheries, and health applications.