The Open Hazards method generally computes probabilities for the occurrence of earthquakes in space and time, and for magnitudes typically larger than M > 5.0.  In addition, the methods can be more specifically applied to compute probabilities for other magnitude ranges.  For example Open Hazards methods have been applied to compute the probabilities for great earthquakes having magnitudes M > 8.0 in regions such as Indonesia where these occur.

Open Hazards validates its forecasts using the same types of statistical testing that are used in the weather/climate/financial forecasting communities.  These tests are used to determine resolution, the ability of a forecast to discriminate between alternative outcomes; reliability, whether the predicted frequency of events matches the observed frequency of events; and sharpness, whether events tend to occur at high forecast probabilities, and no events tend to  occur at low forecast probabilities, in contrast to methods in which events tend to occ

Forecasts are validated by a process called backtesting as well as a process called monitoring.  In backtesting, data from the past are divided into a training period (prior data) and a testing period (posterior data).  Forecasts are made using prior data to forecast events that occur during the posterior interval.  The accuracy of these forecasts are then scored by a variety of statistical tests.  Forecasts that achieve a pre-determined level of accuracy are considered to be validated at the observed confidence level.  In monitorin

The United States Geological Survey, through its Working Groups on California Earthquake Probabilities, has been developing long  term earthquake forecasts for regions in California since 1988.  These forecasts are based on data describing historic averages of major earthquakes as well as paleoseismic geologic data, obtained from trenching studies on active fault traces, and instrumental data.  The result of these studies are 30 year probabilities for major earthquakes, typically having magnitudes M > 6.7, on major earthquake faults in Ca

Yes.  The official forecast for the state of California is a collaboration between the US Geological Survey, the California Geological Survey, and a large group of scientists from universities and commercial companies.  These forecasts are used to set earthquake insurance rates in California.

Probabilistic forecasting involves the computation of a spatial probability density function together with a temporal probability, leading to a  conditional probability.  The latter is the probability that an earthquake of a specified magnitude will occur, conditioned on the observation that no earthquake has occurred in the recent past.  An example of a forecast probability statement might be that "there is a 40% probability that an earthquake having a magnitude between 6.5 and 7.0 will occur within a 20 km radius around location X  during the next 3 months."

While the dictionary defines forecasting to be a synonym for prediction, we consider forecasting to be a specification of the odds, or probability, of an earthquake occurring at a given location, during a given time window, within a given magnitude range.  By contrast, we consider a prediction to be the specification that an earthquake either will, or will not, occur at a given location, during a given time window, within a given magnitude range.  A forecast is therefore a statement of probability, whereas a prediction is a binary statement.  An individual forecast ca