LOCA, which stands for Localized Constructed Analogs, is a technique for downscaling climate model projections of the future climate.
Most climate models have relatively coarse spatial resolution. Which is to say, a single gridcell of a global climate model can cover the distance from San Francisco to Sacramento. If you want to know how temperatures or precipitation might change on finer spatial scales, you need to downscale the climate model output.
The localized constructed analogs (LOCA) method is a statistical scheme that produces downscaled estimates suitable for hydrological simulations using a multi-scale spatial matching scheme to pick appropriate analog days from observations.
First, a pool of candidate observed analog days is chosen by matching the model field to be downscaled to observed days over the region that is positively correlated with the point being downscaled, which leads to a natural independence of the downscaling results to the extent of the domain being downscaled. Then the one candidate analog day that best matches in the local area around the grid cell being downscaled is the single analog day used there.
Most grid cells are downscaled using only the single locally selected analog day, but locations whose neighboring cells identify a different analog day use a weighted combination of the center and adjacent analog days to reduce edge discontinuities. By contrast, existing constructed analog methods typically use a weighted average of the same 30 analog days for the entire domain. By greatly reducing this averaging, LOCA produces better estimates of extreme days, constructs a more realistic depiction of the spatial coherence of the downscaled field, and reduces the problem of producing too many light-precipitation days.
The LOCA method is more computationally expensive than existing constructed analog techniques, but is still practical for downscaling numerous climate model simulations with limited computational resources.
You can get all the details on how LOCA works from material in the bibliography.