Comparison of WPMM vs. regression methods for evaluating Z-R relationships

Daniel Rosenfeld

Comparison of WPMM vs. regression methods for evaluating Z-R relationships

Daniel Rosenfeld^*

^*Corresponding author for this work

Fredy & Nadine Herrmann Institute of Earth Sciences

Research output: Contribution to conference › Paper › peer-review

1 Scopus citations

Abstract

This study shows that, when the scatter is caused by synchronization errors, (Z_e-R) measured reflectivity - Gauge measured rain intensity relations are estimated more accurately by (PMM) the Probability Matching Method as compared to regression. Rosenfeld et al. (1994) took this into account in their Window Probability Matching Method. They allowed Z_e-R pairs within window sizes in time and space which were just large enough to include the uncertainties in synchronization and collocation of the rain gauge with respect to the radar measured volume. This significantly increases the number of Z_e-R pairs and thus the accuracy of the estimated Z_e-R relationship. This study shows that the PMM outperforms regression when such small window synchronization errors are introduced to otherwise perfectly synchronous data set.

Original language	English
Pages	23-25
Number of pages	3
State	Published - 1995
Event	Proceedings of the 1995 27th Conference on Radar Meteorology - Vail, CO, USA Duration: 9 Oct 1995 → 13 Oct 1995

Conference

Conference	Proceedings of the 1995 27th Conference on Radar Meteorology
City	Vail, CO, USA
Period	9/10/95 → 13/10/95

Cite this

@conference{bd8df4b6aca54f39a5c2ab6c6ae3614a,

title = "Comparison of WPMM vs. regression methods for evaluating Z-R relationships",

abstract = "This study shows that, when the scatter is caused by synchronization errors, (Ze-R) measured reflectivity - Gauge measured rain intensity relations are estimated more accurately by (PMM) the Probability Matching Method as compared to regression. Rosenfeld et al. (1994) took this into account in their Window Probability Matching Method. They allowed Ze-R pairs within window sizes in time and space which were just large enough to include the uncertainties in synchronization and collocation of the rain gauge with respect to the radar measured volume. This significantly increases the number of Ze-R pairs and thus the accuracy of the estimated Ze-R relationship. This study shows that the PMM outperforms regression when such small window synchronization errors are introduced to otherwise perfectly synchronous data set.",

author = "Daniel Rosenfeld",

year = "1995",

language = "אנגלית",

pages = "23--25",

note = "Proceedings of the 1995 27th Conference on Radar Meteorology ; Conference date: 09-10-1995 Through 13-10-1995",

}

TY - CONF

T1 - Comparison of WPMM vs. regression methods for evaluating Z-R relationships

AU - Rosenfeld, Daniel

PY - 1995

Y1 - 1995

N2 - This study shows that, when the scatter is caused by synchronization errors, (Ze-R) measured reflectivity - Gauge measured rain intensity relations are estimated more accurately by (PMM) the Probability Matching Method as compared to regression. Rosenfeld et al. (1994) took this into account in their Window Probability Matching Method. They allowed Ze-R pairs within window sizes in time and space which were just large enough to include the uncertainties in synchronization and collocation of the rain gauge with respect to the radar measured volume. This significantly increases the number of Ze-R pairs and thus the accuracy of the estimated Ze-R relationship. This study shows that the PMM outperforms regression when such small window synchronization errors are introduced to otherwise perfectly synchronous data set.

AB - This study shows that, when the scatter is caused by synchronization errors, (Ze-R) measured reflectivity - Gauge measured rain intensity relations are estimated more accurately by (PMM) the Probability Matching Method as compared to regression. Rosenfeld et al. (1994) took this into account in their Window Probability Matching Method. They allowed Ze-R pairs within window sizes in time and space which were just large enough to include the uncertainties in synchronization and collocation of the rain gauge with respect to the radar measured volume. This significantly increases the number of Ze-R pairs and thus the accuracy of the estimated Ze-R relationship. This study shows that the PMM outperforms regression when such small window synchronization errors are introduced to otherwise perfectly synchronous data set.

UR - http://www.scopus.com/inward/record.url?scp=0029429197&partnerID=8YFLogxK

M3 - ???researchoutput.researchoutputtypes.contributiontoconference.paper???

AN - SCOPUS:0029429197

SP - 23

EP - 25

T2 - Proceedings of the 1995 27th Conference on Radar Meteorology

Y2 - 9 October 1995 through 13 October 1995

ER -

Comparison of WPMM vs. regression methods for evaluating Z-R relationships

Abstract

Conference

Other files and links

Fingerprint

Cite this