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Mapping water vapour variability over a mountainous tropical island using InSAR and an atmospheric model for geodetic observations

Webb, T. L., Wadge, G. and Pascal, K. (2020) Mapping water vapour variability over a mountainous tropical island using InSAR and an atmospheric model for geodetic observations. Remote Sensing of Environment, 237. 111560. ISSN 0034-4257

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To link to this item DOI: 10.1016/j.rse.2019.111560

Abstract/Summary

The three dimensional distribution of water vapour around mountainous terrain can be highly variable. This variability can in turn affect local meteorological processes and geodetic techniques to measure ground surface motion. We demonstrate this general problem with the specific issues of a small tropical island, Montserrat. Over a period of 17 days in December 2014 we made observations using InSAR and GPS techniques, together with concurrent atmospheric models using the WRF code. Comparative studies of water vapour distribution and its effect on refractivity were made at high spatial resolution (300 m) over short distances (~10 km). Our results show that model simulations of the observed differences in water vapour distribution using WRF is insufficiently accurate. We suggest that better use could be made of the knowledge and observations of local water vapour conditions at different scales, specifically the Inter Tropical Convergence Zone (ITCZ), the trade wind fields and the mountain flow (~30 m) perhaps using eddy simulation. The annual perturbations of the ITCZ show that the range of humidity is approximately the same expressed as the differential phase of InSAR imaging (~100 mm). Trade wind direction and speed are particularly important at high wind speeds driving vigorous asymmetrical convection over the island's mountains. We also show that the slant angles of radar can follow distinct separate paths through the water vapour field. Our study is novel in demonstrating how synoptic-scale features and climate can advise the modelling of mesoscale systems and sub-seasonal InSAR imaging on tropical islands.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Environmental Systems Science Centre
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:87723
Publisher:Elsevier

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