 |
| Titel |
Half-Hour Rainfall Retrieval based on multispectral geostationary satellite images |
| VerfasserIn |
Yuan Wang, Xiao-Yong Zhuge |
| Konferenz |
EGU General Assembly 2015
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250104845
|
| Publikation (Nr.) |
 EGU/EGU2015-4284.pdf |
|
|
|
|
|
| Zusammenfassung |
| A method for both precipitation area and intensity retrievals is developed based on
multispectral geostationary satellite images. This method can be applied to continuous
observation of large-scale precipitation so as to solve the problem from the measurements of
rainfall radar and rain gauge.
Satellite observation is instantaneous, whereas the rain gauge records accumulative
data during a time interval, and thus, using the 10-min gauge rainfall data rather
than 1-hr gauge rainfall data as the reference value, can obviously improve the
accuracy of satellite rainfall retrieval.For this reason, a 10-min rainfall algorithm is
established firstly. It includes two steps. 1) A Rainfall probability identification
matrix (RPIM) is used to distinguish rainfall clouds from nonrainfall clouds. This
RPIM is established by combining infrared brightness temperatures (BTs) with
visible reflectivity at daytime and dual-channel brightness temperature differences
(BTDs) at nighttime. It is more efficient in improving the retrieval accuracy of rainfall
area than previous threshold combination screening methods. 2) the multispectral
segmented curve-fitting rainfall algorithm (MSCFRA) is proposed to estimate the 10-min
rain rates. Rainfall samples taken from June to August 2008 and 2010 are used to
assess the performance of the rainfall algorithm. Assessment results show that the
MSCFRA improves the accuracy of rainfall estimation for both stratiform cloud
rainfall and convective cloud rainfall. These results are practically consistent with
rain gauge measurements in both rainfall area division and rainfall intensity grade
estimation. Furthermore, this study demonstrates that the temporal resolution of satellite
detection is important and necessary in improving the precision of satellite rainfall
retrieval.
The current geostationary satellite provides an image every half an hour, so the temporal
“gaps” exist when the satellite images are directly used to retrieve 10-min rainfall. To
implement continuous and reliable rainfall retrieval, an immediate tracking and continuous
accumulation technique (ITCAT) of half-hour rainfall retrieval is proposed. The ITCAT
includes two steps. 1) The cross-correlation method is applied to track cloud-motion currents
and establish 10-min-interval image sequences. 2) A continuous retrieval of 10-min rain rate
is conducted with the image sequences, and finally a total half-hour rainfall is determined by
accumulations. The satellite retrieval tests on the typical precipitation process in summer of
2008 show that, compared with the previous direct rainfall retrieval for half-hour to
one-hour, this rainfall retrieval technique significantly improves the retrieval accuracy of
rainfall scope and rainfall intensity ranging from slight rain to rainstorm for both
real-time monitoring or nowcasting processes. This technique is more effective than
the previous algorithm, and the fundamental reason lies in its consideration of the
movement of cloud cluster. On this basis, coverage duration of rainfall clouds can be
reliably estimated. It is of significance to the retrieval of deep convective cloud
rainfall with rapid movement speed and drastic intensity variation. This technique
also provides a feasible idea for improving the accuracy of rainfall nowcasting. |
|
|
|
|
|
|