Detection of the cloud liquid water path horizontal inhomogeneity in a coastline area by means of ground-based microwave observations: feasibility study

Abstract

Abstract. Improvement of cloud modelling for global and regional climate and weather studies requires comprehensive information on many cloud parameters. This information is delivered by remote observations of clouds from ground-based and space-borne platforms using different methods and processing algorithms. Cloud liquid water path (LWP) is one of the main obtained quantities. Previously, measurements of LWP by the SEVIRI (Spinning Enhanced Visible and InfraRed Imager) and AVHRR (Advanced Very High Resolution Radiometer) satellite instruments provided evidence for the systematic differences between LWP values over land and water areas in northern Europe. An attempt is made to detect such differences by means of ground-based microwave observations performed near the coastline of the Gulf of Finland in the vicinity of St Petersburg, Russia. The microwave radiometer (RPG-HATPRO, Radiometer Physics GmbH – Humidity And Temperature PROfiler), located 2.5 km from the coastline, is functioning in the angular scanning mode and is probing the air portions over land (at an elevation angle of 90∘) and over water (at seven elevation angles in the range 4.8–30∘). The influence of the land–sea LWP difference on the brightness temperature values in the 31.4 GHz spectral channel has been demonstrated, and the following features have been detected: (1) an interfering systematic signal is present in the 31.4 GHz channel, which can be attributed to the humidity horizontal gradient, (2) clouds over the opposite shore of the Gulf of Finland mask the LWP gradient effect. Preliminary results of the retrieval of LWP over water by the statistical regression method applied to the microwave measurements by HATPRO in the 31.4 and 22.24 GHz channels are presented. The monthly averaged results are compared to the corresponding values derived from the satellite observations by the SEVIRI instrument and from the reanalysis data.