TY - JOUR
T1 - Inference of spatial scaling properties of rainfall
T2 - Impact of radar rainfall estimation uncertainties
AU - Villarini, Gabriele
AU - Krajewski, Witold F.
N1 - Funding Information:
W. F. Krajewski acknowledges partial support by Rose & Joseph Summers endowment.
Funding Information:
Manuscript received April 6, 2009; revised May 11, 2009. First published August 7, 2009; current version published October 14, 2009. The work of G. Villarini was supported by NASA Headquarters under the Earth Science Fellowship Grant NNX06AF23H while a graduate student at the University of Iowa.
PY - 2009/10
Y1 - 2009/10
N2 - The existence of relationships able to connect quantities across different spatio-temporal scales represents an attractive way of describing and characterizing the high spatial and temporal variability of the rainfall process. Several studies investigated the scaling properties of spatial rainfall, and in most of the cases, these analyses were performed using radar-based estimates of rainfall, which are notoriously affected by systematic and random uncertainties. The impact of these errors on the estimated scaling properties of spatial rainfall still remains an open question. By using an empirically based radar rainfall error model, the authors explore this issue by generating ensembles of probable true rainfall fields, conditioned on radar rainfall maps. Fifteen rainfall events over Oklahoma are analyzed, and it is shown how the presence of radar rainfall errors results in biased estimates of the scaling properties of rainfall.
AB - The existence of relationships able to connect quantities across different spatio-temporal scales represents an attractive way of describing and characterizing the high spatial and temporal variability of the rainfall process. Several studies investigated the scaling properties of spatial rainfall, and in most of the cases, these analyses were performed using radar-based estimates of rainfall, which are notoriously affected by systematic and random uncertainties. The impact of these errors on the estimated scaling properties of spatial rainfall still remains an open question. By using an empirically based radar rainfall error model, the authors explore this issue by generating ensembles of probable true rainfall fields, conditioned on radar rainfall maps. Fifteen rainfall events over Oklahoma are analyzed, and it is shown how the presence of radar rainfall errors results in biased estimates of the scaling properties of rainfall.
KW - Error analysis
KW - Radar
KW - Rain
KW - Scaling
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U2 - 10.1109/LGRS.2009.2025891
DO - 10.1109/LGRS.2009.2025891
M3 - Article
AN - SCOPUS:70350346051
SN - 1545-598X
VL - 6
SP - 812
EP - 815
JO - IEEE Geoscience and Remote Sensing Letters
JF - IEEE Geoscience and Remote Sensing Letters
IS - 4
M1 - 5196723
ER -