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Evaluation of PERSIANN-CCS rainfall measurement using the NAME event rain gauge network
پدید آورنده
Hong, Y; Gochis, D; Cheng, JT; Hsu, KL; Sorooshian, S
موضوع
رده
کتابخانه
Center and Library of Islamic Studies in European Languages
محل استقرار
استان:
Qom
ـ شهر:
Qom
تماس با کتابخانه :
32910706
-
025
NATIONAL BIBLIOGRAPHY NUMBER
Number
LA4417p73x
TITLE AND STATEMENT OF RESPONSIBILITY
Title Proper
Evaluation of PERSIANN-CCS rainfall measurement using the NAME event rain gauge network
General Material Designation
[Article]
First Statement of Responsibility
Hong, Y; Gochis, D; Cheng, JT; Hsu, KL; Sorooshian, S
SUMMARY OR ABSTRACT
Text of Note
Robust validation of the space-time structure of remotely sensed precipitation estimates is critical to improving their quality and confident application in water cycle-related research. In this work, the performance of the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) precipitation product is evaluated against warm season precipitation observations from the North American Monsoon Experiment (NAME) Event Rain Gauge Network (NERN) in the complex terrain region of northwestern Mexico. Analyses of hourly and daily precipitation estimates show that the PERSIANN-CCS captures well active and break periods in the early and mature phases of the monsoon season. While the PERSIANN-CCS generally captures the spatial distribution and timing of diurnal convective rainfall, elevation-dependent biases exist, which are characterized by an underestimate in the occurrence of light precipitation at high elevations and an overestimate in the occurrence of precipitation at low elevations. The elevation-dependent biases contribute to a 1-2-h phase shift of the diurnal cycle of precipitation at various elevation bands. For reasons yet to be determined, the PERSIANN-CCS significantly underestimated a few active periods of precipitation during the late or "senescent" phase of the monsoon. Despite these shortcomings, the continuous domain and relatively high spatial resolution of PERSIANN-CCS quantitative precipitation estimates (QPEs) provide useful characterization of precipitation space-time structures in the North American monsoon region of northwestern Mexico, which should prove useful for hydrological applications. © 2007 American Meteorological Society.
SET
Date of Publication
2007
Title
UC Irvine
ELECTRONIC LOCATION AND ACCESS
Electronic name
مطالعه متن کتاب
[Article]
275578
a
Y
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