A novel approach to fog/low stratus detection using Meteosat 8 data

Čermák, Jan; Bendix, Jörg

doi:10.1016/j.atmosres.2007.11.009

Cited by 128 publications

(127 citation statements)

References 31 publications

Supporting

Mentioning

127

Contrasting

Order By: Relevance

“…There is substantial diversity in the definition of remotely sensed LSC products. Low stratus and fog covers might be combined due to their similar spectral signatures [10,11] or additional effort can be made to delineate only the conditions with reduced horizontal visibility [12]. In this study these categories are treated together as the LSC.…”

Section: Introductionmentioning

confidence: 99%

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

et al. 2014

View full text Add to dashboard Cite

The near-real time retrieval of low stratiform cloud (LSC) coverage is of vital interest for such disciplines as meteorology, transport safety, economy and air quality. Within this scope, a novel methodology is proposed which provides the LSC occurrence probability estimates for a satellite scene. The algorithm is suited for the 1 × 1 km Advanced Very High Resolution Radiometer (AVHRR) data and was trained and validated against collocated SYNOP observations. Utilisation of these two combined data sources requires a formulation of constraints in order to discriminate cases where the LSC is overlaid by higher clouds. The LSC classification process is based on six features which are first converted to the integer form by step functions and combined by means of bitwise operations. Consequently, a set of values reflecting a unique combination of those features is derived which is further employed to extract the LSC occurrence probability estimates from the precomputed look-up vectors (LUV). Although the validation analyses confirmed good performance of the algorithm, some inevitable misclassification with other optically thick clouds were reported. Moreover, the comparison against Polar Platform System (PPS) cloud-type product revealed superior classification accuracy. From the temporal perspective, the acquired results reported a presence of diurnal and annual LSC probability cycles over Europe.

show abstract

Section: Introductionmentioning

confidence: 99%

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Several studies have tested daytime fog detection using these basic approaches [e.g. Bendix et al, 2005;Cermak and Bendix, 2008).…”

Section: Introductionmentioning

confidence: 99%

Validation of a Satellite-based Fog and Low Stratus Detection Algorithm Using Himawari-8 over Australia

Lucas¹

2017

Bureau Research Report

View full text Add to dashboard Cite

“…A major problem with numerical models is the uncertainty in the parameterization of turbulence and microphysical processes, as the processes involved are not fully understood and there is a lack of empirical data that could provide better information [7]. One problem with satellite-based nowcasting methods is the reliable distinction between ground fog and low stratus layers [8]. Bendix et al [9] and Cermak and Bendix [10] used (sub)adiabatic approximations of the vertical liquid water content (LWC) profile to retrieve cloud thickness, which, in turn, was used for the distinction between ground fog and low stratus layers.…”

Section: Introductionmentioning

confidence: 99%

The Influence of Drop Size Distributions on the Relationship between Liquid Water Content and Radar Reflectivity in Radiation Fogs

2017

Self Cite

View full text Add to dashboard Cite

This study investigates the temporal dynamics of the drop size distribution (DSD) and its influence on the relationship between the liquid water content (LWC) and the radar reflectivity (Z) in fogs. Data measured during three radiation fog events at the Marburg Ground Truth and Profiling Station in Linden-Leihgestern, Germany, form the basis of this analysis. Specifically, we investigated the following questions: (1) Do the different fog life cycle stages exhibit significantly different DSDs? (2) Is it possible to identify characteristic DSDs for each life cycle stage? (3) Is it possible to derive reliable Z-LWC relationships by means of a characteristic DSD? The results showed that there were stage-dependent differences in the fog life cycles, although each fog event was marked by unique characteristics, and a general conclusion about the DSD during the different stages could not be made. A large degree of variation within each stage also precludes the establishment of a representative average spectrum.

show abstract

A novel approach to fog/low stratus detection using Meteosat 8 data

Cited by 128 publications

References 31 publications

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

Daytime Low Stratiform Cloud Detection on AVHRR Imagery

Validation of a Satellite-based Fog and Low Stratus Detection Algorithm Using Himawari-8 over Australia

The Influence of Drop Size Distributions on the Relationship between Liquid Water Content and Radar Reflectivity in Radiation Fogs

Contact Info

Product

Resources

About