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The urban heat island (UHI) effect is one of the typical characteristics of urban climate, which makes a lot of harmful gases accumulate and cannot be diffused. The UHI effect will cause air pollution, affecting the health and living conditions of humans. In this paper, a new method for calculating UHI intensity (UHII) by using the Global Navigation Satellite Systems (GNSS) derived zenith tropospheric delay (GNSS-ZTD) dataset and atmospheric empirical model was proposed and tested by using UHII observations from ground meteorological sensors for monitoring UHII in the Hong Kong city. The method requires accurate GNSS-ZTD datasets, priori atmospheric parameters (i.e. ground pressure and water vapour partial pressure) and the coefficient of the refractive function as inputs. The GNSS-ZTD datasets were obtained by using observations from the Hong Kong GNSS continuously operating reference stations network, and priori atmospheric parameters were obtained from a prior atmospheric model based on ERA5 (fifth-generation reanalysis dataset of the European Centre for Medium-range Weather Forecasting) dataset and the coefficient of the refractive function can be obtained from the historical radiosondes data. The ground refractivity, pressure and water vapour partial pressure can be estimated by using the above-mentioned datasets, then the time series of UHII can be obtained by using a refractivity model proposed by Smith and Weintraub (SW-UHII), or Thayer (Thayer-UHII model). The results showed that the accuracy of the SW-UHII is better than the accuracy of the Thayer-UHII, and the root mean square (RMS) of the SW-UHII is 14% lower than the RMS of the Thayer-UHII. The mean bias, RMS and standard deviation of the SW-UHII compared with meteorological data derived UHII over GNSS stations are 1.82°C, 1.9°C and 1.41°C in all seasons, respectively, and the largest RMS is in winter (day of year 1–61 and 331–365). All the above results indicated that the GNSS technique has a certain prospect for monitoring UHII.

A new method for retrieving urban heat island intensity using GNSS-derived ZTD and atmospheric empirical model