A 10 year cloud climatology over Scandinavia derived from NOAA Advanced Very High Resolution Radiometer imagery

Abstract

Results from a satellite-based method to compile regional cloud climatologies covering the Scandinavian region are presented. Systematic processing of multispectral image data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) instrument has been utilized to provide monthly cloud climatologies covering the period 1991-2000. Considerable local-scale variation of cloud amounts was found in the region. The inland Baltic Sea and adjacent land areas exhibited a large-amplitude annual cycle in cloudiness (high cloud amounts in winter, low cloud amounts in summer) whereas a weak-amplitude reversed annual cycle (high cloud amounts with a weak maximum in summer) was found for the Scandinavian mountain range. As a contrast, conditions over the Norwegian Sea showed high and almost unchanged cloud amounts during the course of the year. Some interesting exceptions to these patterns were also seen locally. The quality of the satellite-derived cloud climatology was examined through comparisons with climatologies derived from surface cloud observations, from the International Satellite Cloud Climatology Project (ISCCP) and from the European Centre for Medium-range Weather Forecasts ERA-40 data set. In general, cloud amount deviations from surface observations were smaller than 10% except for some individual winter months, when the separability between clouds and snow-covered cold land surfaces is often poor. The ISCCP data set showed a weaker annual cycle in cloudiness, generally caused by higher summer-time cloud amounts in the region. Very good agreement was found with the ERA-40 data set, especially for the summer season. However, ERA-40 showed higher cloud amounts than SCANDIA and ISCCP during the winter season. The derived cloud climatology is affected by errors due to temporal AVHRR sensor degradation, but they appear to be small for this particular study. The data set is proposed as a valuable data set for validation of cloud description in numerical weather prediction and regional climate simulation models.

Influence of ice particle model on satellite ice cloud retrieval: lessons learned from MODIS and POLDER cloud product comparison

“…But why does POLDER retrieval tend to be smaller? The underlying physics is as follows: It has been shown that the observed cloud reflectivity at a non-absorbing wavelength, such as the 0.86µm, is generally proportional to the scaled optical thickness, (1 − g)τ , (van de Hulst, 1980;King, 1987). In other words, the retrieved τ is proportional to 1/(1 − g).…”

“…It plays a key role in determining cloud radiative forcing (CRF) (e.g., Fu and Liou, 1993;Jensen et al, 1994;Fu, 1996;Fu et al, 1998;McFarquhar et al, 2000). A popular method to retrieve cloud τ relies on satellite measurements of the Earth's reflected shortwave radiance (King, 1987;Nakajima and King, 1990;Minnis et al, 1993) (Hereafter it is referred to as the "solar reflective method"). It has been employed in the retrieval algorithms of several satellite instruments, such as the Advanced Very High Resolution Radiometer (AVHRR) (Heidinger et al, 2005), Spinning Enhanced Visible and Infrared Imager (SEVIRI) (Roebeling et al, 2006), MODIS (Platnick et al, 2003) and POLDER (Buriez et al, 2005).…”

“…As a result, different satellite sensors may produce different τ retrievals for the same cloud. Such differences complicate our understanding of the climatic role of ice clouds due to the fact that satellite retrievals are now widely used, for example, to derive cloud climatologies (Rossow and Schiffer, 1999;Karlsson, 2003) and compare with GCM simulations (Zhang et al, 2005). Therefore, a study of the influences of the above factors, especially the ice particle model in ice cloud τ retrieval would help us to understand the differences of ice τ retrievals from different sensors and may improve our understanding of ice clouds.…”

Total suspended matter derived from MERIS data as indicator for coastal processes in the Baltic Sea

“…Because of its improved spatial and spectral resolution, it was capable to sense the dynamical changes in coastal water quality, and it also has been shown to improve the temporal resolution of water monitoring programs Harvey et al, 2015), even in areas with relatively frequent cloud cover, such as the Baltic Sea (Isemer and Rozwadowska, 1999;Karlsson, 2003). 30 One parameter that can be used to identify the extent of the coastal zone is total suspended matter (TSM), which also can be detected from space using ocean colour remote sensing data.…”

Correcting orbital drift signal in the time series of AVHRR derived convective cloud fraction using rotated empirical orthogonal function

“…These long-term measurements at high spatio-temporal resolution and at carefully chosen spectral wavelengths make them extremely valuable for climate monitoring purposes and process-based studies (Rossow and Schiffer, 1999;Karlsson, 2003;Heidinger and Pavolonis, 2009;Schulz et al, 2009). The AVHRR data in principle could be used for investigating variability and trends in essential climate variables at the decadal time scales.…”