Cite as:
High spatiotemporal resolution of Rainfall in Iran <small>by Turini, N.; Thies, B. &amp; Bendix, J. (2019)</small>

Resource Description

Title: High spatiotemporal resolution of Rainfall in Iran
Short Name: Rainfall in Iran
FOR816dw ID: 430
Publication Date: 2019-09-24
Last Update Date: 2021-06-03
License and Usage Rights: LCRS
Temporal Coverage:
Begin: 2017-02-01
End: 2018-02-02
Geographic Coverage:
Geographic Description: Iran
Bounding Coordinates:
- lon/lat [degrees]
- WGS 84
North: Information not publicly available, please log in. Max: 5610.0 ( meter )
West: Information not publicly available, please log in. East: Information not publicly available, please log in. Elevation
South: Information not publicly available, please log in. Min: -28.0 ( meter )
Dataset Owner(s):
Individual: Nazli Turini
Individual: Boris Thies
Individual: Jörg Bendix
A new satellite-based technique for rainfall retrieval in high spatio-temporal resolution (3 km, 15 min) for Iran is presented. The algorithm is based on the infrared bands of the Meteosat Second Generation Spinning Enhanced Visible and Infrared Imager (MSG SEVIRI). Random forest models using microwave-only rainfall information of the Integrated Multi-SatEllite Retrieval for the Global Precipitation Measurement (GPM) (IMERG) product as a reference were developed to (i) delineate the rainfall area and (ii) to assign the rainfall rate. The method was validated against independent microwave-only GPM IMERG rainfall data not used for model training. Additionally, the new technique was validated against completely independent gauge station data. The validation results show a promising performance of the new rainfall retrieval technique, especially when compared to the GPM IMERG IR-only rainfall product. The standard verification scored an average Heidke Skill Score of 0.4 for rain area delineation and an average R between 0.1 and 0.7 for rainfall rate assignment, indicating uncertainties for the Lut Desert area and regions with high altitude gradients
| rainfall retrieval | rainfall | Rainfall rate | satellite-based rainfall detection scheme |
Associated entities to this dataset:
-------- 1 . other entity --------
Entity name: iran_1_hist_hydromet_tp_20170201_20180201
Entity Description: High Spatio-temporal resolution of rainfall in Iran
Tech. Details ...
Attribute(s) ...
Metadata Provider:
Individual: Nazli Turini
Contact Person:
Individual: Nazli Turini
Online Distribution:
Download File:
Data Publisher:
Organization: LCRS - Laboratory for Climatology and Remote Sensing

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