High-ResolutionGOES-8Visible and Infrared Cloud Frequency Composites over Northern Florida during the Summers 1996–99

Abstract

GOES-8 visible and infrared cloud frequency composites have been created from imagery collected during June, July, and August for the years 1996-99 over northern Florida. These cloud frequency composites are unique because they offer high-resolution coverage over a small area and have been tailored to address forecast needs. Both monthly and regime cloud frequency composites are presented. Nine regimes were designated to reflect the strength and development of the sea-breeze front under various synoptic winds and the resulting effect on convective development. The regimes were designated by mean boundary layer wind speed and direction over the region of interest. Results from four of the regimes are presented.A total of 222 days (60% of all possible days) were designated for the various wind regimes. Regime 4 (W to SW flow) occurred most frequently (24%) and had the most widespread distribution of higher cloud frequency, occurring both near the coast and inland. Regime 2, with contrasting E to NE flow, was the next most frequently occurring regime (17%) and had lower cloud frequencies, particularly inland in Alabama and Georgia. Regime 5, with strong W to SW flow (15%, not presented) was third, followed by Regime 8 with N to NW flow (13%) and Regime 1 (11%) with light and variable or light SE flow.The monthly composites included the days from the various regime days as well as those with a completely disturbed or completely suppressed sea-breeze circulation. Nonetheless, the influence of the sea-breeze circulation can readily be seen in the diurnal progression of cloud frequency over a month. The variations seen in monthly cloud frequency composites for June, July, and August 1996-99 highlight periods of high and low cloud frequency and offer a different perspective on year-to-year and month-to-month variability.The regime cloud frequency results are actively being used during the summer season in aviation and public forecasting to supplement available information.

Sea-Breeze Convergence Zones from AVHRR over the Iberian Mediterranean Area and the Isle of Mallorca, Spain

“…The prevailing low-level boundary layer wind has been shown to be the most influential factor on sea-breeze evolution (e.g., Estoque 1962;Blanchard and Ló pez 1985;Bechtold et al 1991;Gould and Fuelberg 1996;Connell et al 2001). Upper-air observations recorded at Murcia (station 80430, southeastern IP; Fig.…”

“…The high-resolution visible (VIS) and infrared (IR) satellite imagery composites are powerful tools for observing the timing, location, and intensity of convection associated with sea-breeze fronts (e.g., Connell et al 2001). Sea-breeze complex interactions (e.g., Simpson 1994), as exemplified by the features of the coastline, the small-scale terrain, and the large-scale flows, make the short-term forecast difficult (e.g., González Márquez and Heredia 2001).…”

“…Gould and Fuelberg (1996) and Connell et al (2001) focused their investigations on the sea-breeze cloud climatology over the Florida Panhandle. Their results are being used in short-range forecasts for meteorology, maritime, and aviation applications.…”

Fuzzy rule based approaches for cloud cover estimation using Meteosat 5 images

“…Except in very unusual situations, for any region we are not likely to have cloudy or snow covered images for the entire period. Consequently the background image thus produced will represent a clear-sky condition [2,3] with high confidence. The difference from cloud-free background at every pixel is selected as a feature which represents the temporal characteristic of the data.…”

“…This information has been primarily used by numerical climate modeling community. Most of the available satellite cloud cover estimation algorithms use some threshold mechanism [2,3] or some other statistical methods for separating cloudy pixels from cloud free ones [2,4,5]. But unfortunately these methods often suffer due to the dependence of the images on surface properties; the situation becomes more complex due to the presence of partially or broken/mixed cloud cover pixels.…”