Li, H.; Xu, F., and Wan, F., 2020. Prediction and analysis of the temperature of British Seas in the next 50 years based on the Grey Model. In: Liu, X. and Zhao, L. (eds.), Today's Modern Coastal Society: Technical and Sociological Aspects of Coastal Research. Journal of Coastal Research, Special Issue No. 111, pp. 7–15. Coconut Creek (Florida), ISSN 0749-0208.

The increase in temperature in the surface of the ocean will cause great changes in the living environment of fish. The increase in temperature will reduce the solubility of carbon dioxide, the insufficient absorption of carbon in seawater, and will decrease the concentration of dissolved oxygen. Most fish will migrate, and in view of the current global warming trend, they will gradually move their habitats to more suitable temperature areas. To predict the effect of this temperature change on human production and life, we established two mathematical models to predict the temperature and the number of two economic fish populations. Model 1 addresses how quickly the waters around Scotland changed from 1980 to 2070. We used the sea-surface temperature data from the National Aeronautics and Space Administration Ocean Color website for the past 40 years to make predictions for the next 50 years. The Grey prediction model was used to complete a small data sample on the time series to predict a large unknown amount of data. To illustrate the prediction process, a single-point prediction process is chosen as an example. The forecast result isotherms of all forecast areas are also provided. Model 2 uses the data from Model 1. First, the relationship between temperature changes and the number of fish is studied. The quantity of fish that fishermen can catch in the sea area under the best and worst conditions is given, including the time for small fisheries companies to be bankrupt. In the forecasting process, fish living temperature data from the Fishbase website was obtained and a function between temperature and population was established according to a normal distribution model. Furthermore, the minimum fish density and its arriving time, which can make a small fishery company bankrupt under the temperature change, are also completed.