26 Jul 2022
26 Jul 2022
Status: this preprint is open for discussion.

Monitoring Urban Heat Island Intensity with Ground-based GNSS Observations and Space-based Radio Occultation and Radiosonde Historical Data

Pengfei Xia1, Wei Peng2, Shirong Ye1, Min Guo3, and Fangxin Hu1 Pengfei Xia et al.
  • 1GNSS Research Center, Wuhan University, Wuhan 430079, China
  • 2Faculty of Engineering and applied science, University of Regina, Regina, Saskatchewan, Canada
  • 3School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China

Abstract. Since Urban Heat Islands (UHI) not only negatively impact human health but consume more energy when cooling buildings, accurate monitoring of its impact is critical. In this study, we propose a ground based GNSS technique to fuse GNSS Radio Occultation (RO) and radiosonde products to monitor the UHI intensity, which described as follows: First, the first and second grid tops are defined using the historical RO and radiosonde products. Then, the wet refractivity between the first and second grid tops is fitted to the higher-order spherical harmonic function based on the RO and radiosonde products, and they are used as the inputs of GNSS tomography, which can reduce the number of unknowns voxels of tomography while increasing the effective number of satellite rays, and improving the accuracy of tomography results. Next, according to the relationships among wet refractivity, temperature, and water vapor partial, as well as the function relationships among temperature, wet pressure, and height in adjacent vertical layers, the temperature and water vapor partial pressure can be obtained using the best search method according to the tomography-derived wet refractivity. Finally, the UHI intensity is monitored by the temperature difference between the urban regions and the surrounding rural regions. The radio occultation and radiosonde products of the Hong Kong region from 2010 to 2019, and the observed GNSS network data of the Hong Kong region for the year of 2020 are employed to evaluate the UHI intensity algorithm. The validation of the algorithm is done by comparing the UHI intensity estimated from the algorithm with the temperature data obtained from weather stations. The result shows that the proposed algorithm can achieve an accuracy of 1.2 K at a 95 % confidence level.

Pengfei Xia et al.

Status: open (until 20 Sep 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on egusphere-2022-589', Zhounan Dong, 05 Aug 2022 reply
  • CC2: 'Comment on egusphere-2022-589', xianjie Li, 05 Aug 2022 reply

Pengfei Xia et al.

Pengfei Xia et al.


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Short summary
We first present a novel method of monitoring the UHI intensity using GNSS data. We overcomes two major challenges in the algorithm development. The first challenge is the determination of the GNSS tomographic top grid height, and the second challenge is the estimation of temperature from wet refractivity. The result shows that the proposed algorithm can achieve an accuracy of 1.2 K at a 95 % confidence level.