The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts.

LCAT is an online interactive tool that will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems.

Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices.

The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.