email:
bendix <at> staff.uni-marburg.de
Deutschhausstraße 12
Room No. 02 A 48
35032 Marburg
Faculty of Geography
Germany
Abstract:
A new satellite-based algorithm for rainfall retrieval in high spatio-temporal resolution for Ecuador is presented. The algorithm relies on the precipitation information from the Integrated Multi-SatEllite Retrieval for the Global Precipitation Measurement (GPM) (IMERG) and infrared (IR) data from the Geostationary Operational Environmental Satellite-16 (GOES-16). It was developed to (i) classify the rainfall area (ii) assign the rainfall rate. In each step, we selected the most important predictors and hyperparameter tuning parameters monthly. Between 19 April 2017 and 30 November 2017, brightness temperature derived from the GOES-16 IR channels and ancillary geo-information were trained with microwave-only IMERG-V06 using random forest (RF). Validation was done against independent microwave-only IMERG-V06 information not used for training. The validation results showed the new rainfall retrieval technique (multispectral) outperforms the IR-only IMERG rainfall product.
Keywords:
| rainfall | Geostationary satellites | multispectrl satellite data |
Associated entities to this dataset:
--------
1
. other entity --------
Entity name:
High spatiotemporal resolution of Rainfall in Ecuador
Entity Description:
Tech. Details ...
Physical Structure Description:
Object Name:
ecuador_hist_hydromet_tp_19042017_19042018.nc
Size (byte):
225239606
External Format:
High spatiotemporal resolutio
2020
Attribute(s) ...
Attribute Name -- Attribute Label
Unit
Attribute definition
Metadata Provider:
Individual:
Nazli Turini
Contact:
email:
turini <at> staff.Uni-Marburg.DE
Germany
Contact Person:
Individual:
Nazli Turini
Contact:
email:
turini <at> staff.Uni-Marburg.DE
Germany
Online Distribution:
Download File:
http://www.lcrs.de/data_pre.do?citid=448
Data Publisher:
Organization:
LCRS - Laboratory for Climatology and Remote Sensing
