Orellana-Alvear, J.; Celleri, R.; Rollenbeck, R. & Bendix, J. (2019): <b>Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model</b>. <i>Remote Sensing</i> <b>11</b>(14), 1632.
Resource Description
Title:
Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model
FOR816dw ID:
1748
Publication Date:
2019-01-01
License and Usage Rights:
Resource Owner(s):
Individual:
Johanna Orellana-Alvear
Contact:
email:
webmaster <at> tropicalmountainforest.org
Individual:
Rolando Celleri
Contact:
email:
rcelleri <at> gmail.com
Dirección de Investigación
Cuenca
Ecuador
Individual:
Ruetger Rollenbeck
Contact:
email:
rollenbe <at> staff.uni-marburg.de
Laboratory for Climatology and Remote Sensing
Faculty of Geography
Philipps University of Marburg
Deutschhausstr. 10
35032 Marburg
Germany
Individual:
Jörg Bendix
Contact:
email:
webmaster <at> tropicalmountainforest.org
Abstract:
Despite many eorts of the radar community, quantitative precipitation estimation (QPE)<br/>
from weather radar data remains a challenging topic. The high resolution of X-band radar imagery<br/>
in space and time comes with an intricate correction process of reflectivity. The steep and high<br/>
mountain topography of the Andes enhances its complexity. This study aims to optimize the rainfall<br/>
derivation of the highest X-band radar in the world (4450 m a.s.l.) by using a random forest (RF)<br/>
model and single Plan Position Indicator (PPI) scans. The performance of the RFmodel was evaluated<br/>
in comparison with the traditional step-wise approach by using both, the Marshall-Palmer and a<br/>
site-specific Z–R relationship. Since rain gauge networks are frequently unevenly distributed and<br/>
hardly available at real time in mountain regions, bias adjustment was neglected. Results showed an<br/>
improvement in the step-wise approach by using the site-specific (instead of the Marshall-Palmer)<br/>
Z–R relationship. However, both models highly underestimate the rainfall rate (correlation coecient<br/>
< 0.69; slope up to 12). Contrary, the RF model greatly outperformed the step-wise approach in<br/>
all testing locations and on dierent rainfall events (correlation coecient up to 0.83; slope = 1.04).<br/>
The results are promising and unveil a dierent approach to overcome the high attenuation issues<br/>
inherent to X-band radars.
Keywords:
| South Ecuador | random forest | radar | calibration | Cajas National Park |
Literature type specific fields:
ARTICLE
Journal:
Remote Sensing
Volume:
11
Issue:
14
Page Range:
1632
Metadata Provider:
Individual:
Jörg Bendix
Contact:
email:
bendix <at> staff.uni-marburg.de
Faculty of Geography
Deutschhausstraße 10
Philipps University of Marburg
Laboratory for Climatology and Remote Sensing
35032 Marburg
Germany
