Abstract
Abstract. A new technique for process-oriented rain area classification using Meteosat Second Generation SEVIRI nighttime data is introduced. It is based on a combination of the Advective Convective Technique (ACT) which focuses on precipitation areas connected to convective processes and the Rain Area Delineation Scheme during Nighttime (RADS-N) a new technique for the improved detection of stratiform precipitation areas (e.g. in connection with mid-latitude frontal systems). The ACT which uses positive brightness temperature differences between the water vapour (WV) and the infrared (IR) channels (ΔTWV-IR) for the detection of convective clouds and connected precipitating clouds has been transferred from Meteosat First Generation (MFG) Metesoat Visible and Infra-Red Imager radiometer (MVIRI) to Meteosat Second Generation (MSG) Spinning Enhanced Visible and InfraRed Imager (SEVIRI). RADS-N is based on the new conceptual model that precipitating cloud areas are characterised by a large cloud water path (cwp) and the presence of ice particles in the upper part of the cloud. The technique considers information about both parameters inherent in the channel differences ΔT3.9-10.8, ΔT3.9-7.3, ΔT8.7-10.8, and ΔT10.8-12.1, to detect potentially precipitating cloud areas. All four channel differences are used to gain implicit knowledge about the cwp. ΔT8.7-10.8 and ΔT10.8-12.1 are additionally considered to gain information about the cloud phase. First results of a comparison study between the classified rain areas and corresponding ground based radar data for precipitation events in connection with a cold front occlusion show encouraging performance of the new proposed process-oriented rain area classification scheme.
Highlights
The estimation of precipitation by means of geostationary weather satellites has a long tradition as they provide areawide information about the distribution of this major factor of the global water cycle in a spatially and temporally high resolution.Most of the retrieval techniques developed so far rely on the relationship between cloud top temperature in the infrared channel and the rainfall probability and rate (e.g. Adler and Negri, 1988)
Such IR retrievals are appropriate for deep convective clouds that can be identified in the infrared and/or water vapour channels (e.g. Levizzani et al, 2001; Levizzani, 2003) but show considerable drawbacks in the mid-latitudes (e.g. Ebert et al, 2007; Fruh et al, 2007), where great parts of the precipitation originates from clouds formed by widespread frontal lifting processes in connection with extra-tropical cyclones
The module for the detection of enhanced advectivestratiform precipitating cloud areas (4) associated to convective precipitation processes in the upper parts of the cloud is based on an iterative k-means clustering algorithm (Bradley and Fayyad, 1998) that is applied to TIR, TWV and a synthetic channel representing the standard deviation of 3 by 3 pixels in the IR channel (StdvIR)
Summary
The estimation of precipitation by means of geostationary weather satellites has a long tradition as they provide areawide information about the distribution of this major factor of the global water cycle in a spatially and temporally high resolution. 1997) which uses the positive brightness temperature difference between the water vapour (WV) and the infrared (IR) channels ( TWV−IR) of MVIRI (see Schmetz et al, 1997; Tjemkes et al, 1997) for a more reliable detection of deep convective clouds (Kurino, 1997). This still leads to an underestimation of the detected rain area, because precipitation fields formed by widespread uplifting processes in connection with extratropical cyclones which are not connected with convective processes (hereafter referred to as advective-stratiform background precipitation; refer to Houze, 1993) are omitted In this context Thies et al (2008) introduced a new rain area delineation scheme during nighttime for MSG SEVIRI which is based on the new conceptual model that precipitating cloud areas are characterised by a sufficiently large cloud water path (cwp) and the existence of ice particles in the upper cloud parts. The effectual transfer of the ACT to MSG SEVIRI and its combination with RADS-N enable the process-oriented classification of the identified rainfall area
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