资源环境科技发展态势分析平台

Air-moisture maps were generated based on commercial microwave links data over N. Israel and compared for the first time to European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim maps for April 2017. Several skill scores of the different maps were calculated against the observed humidity from 39 weather stations. High correlations range, 0.75-0.9, were found between the new links' humidity fields and the stations. The numbers of best correlated links are found to be higher compared to ECMWF, that is, 31 stations versus 8. Also, in the measure of standard deviation the links performed better, 38 versus 1. However, for the mean humidity, the ECMWF is doing better, that is 14/25 for links/ECMWF. The links' humidity thus provides a more accurate picture of the observed moisture as compared to current weather prediction product. Consequently, the high-resolution humidity fields obtained from the commercial microwave link seem to have the potential to improve future forecasting of precipitation.

Plain Language Summary Atmospheric humidity has a cardinal part in weather prediction. Weather forecasting heavily relies on atmospheric models, the accuracy of which is largely determined by the quality of the measurements used for its input. Current humidity measuring tools cannot effectively provide the ideal requirements for weather prediction purposes. The method presented here provides a unique way of obtaining this type of high-resolution measurements, based on data collected by cellular networks. Since the humidity disturbs the signals between two antennas, it can be measured based on information on the signal. In this research, cellular humidity maps were generated for the first time. The maps were compared to products from a well-known forecast model, the European Centre for Medium-Range Weather Forecasts. The cellular humidity maps showed better correlations with weather stations, which represent the real humidity in the air. Good results were obtained also for other statistical skills, indicating the quality and the accuracy of the cellular measurements. The humidity derived from the cellular network was found to be more accurate as compared to the forecast models. Consequently, the new humidity-measuring method is likely to improve in the future the weather prediction, with particular relevance to heavy rainfall.