ABSTRACT:A daytime over land multispectral cloud detection algorithm is presented to derive accurate convective cloud climatologies with high spatial resolution (1.1 km) over the Iberian Peninsula (IP) and the Balearic Islands (BI). The cloud detection scheme was designed to process Advanced Very High Resolution Radiometer (AVHRR) HRPT data and is tested here on NOAA-17 morning (0900-1200 UTC) and NOAA-16 afternoon (1200-1500 UTC) overpasses for the warm 6-month study period May-October. The algorithm consists of four spectral threshold tests applied to each pixel. Test 1 corresponds to the snow-ice removal, test 2 is the thermal infrared test, test 3 is the albedo or visible test and test 4 is the ratio between near-infrared and visible channels. The algorithm discretizes all AVHRR data into four groups called cloud-filled, cloud-free, snow-ice and snow-free radiances. The high-resolution convective cloud masks are obtained by subtracting snow-ice pixels from cloudy ones. In this article, a detailed description of the convective cloud detection scheme and the sources of error detected for each test are given, and the first seasonal and monthly regional convective cloud frequency composites are presented. Future applications of the newly proposed threshold algorithm in climate and meteorology are also discussed in this article, particularly the production of convective cloud composites for climate monitoring of storms over the IP and BI.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.