 |
| Titel |
Multiplicative cascade models for fine spatial downscaling of rainfall: parameterization with rain gauge data |
| VerfasserIn |
D. E. Rupp, P. Licznar, W. Adamowski, M. Leśniewski |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 16, no. 3 ; Nr. 16, no. 3 (2012-03-06), S.671-684 |
| Datensatznummer |
250013203
|
| Publikation (Nr.) |
 copernicus.org/hess-16-671-2012.pdf |
|
|
|
|
|
| Zusammenfassung |
| Capturing the spatial distribution of high-intensity rainfall over
short-time intervals is critical for accurately assessing the efficacy of
urban stormwater drainage systems. In a stochastic simulation framework, one
method of generating realistic rainfall fields is by multiplicative random
cascade (MRC) models. Estimation of MRC model parameters has typically
relied on radar imagery or, less frequently, rainfall fields interpolated
from dense rain gauge networks. However, such data are not always available.
Furthermore, the literature is lacking estimation procedures for spatially
incomplete datasets. Therefore, we proposed a simple method of calibrating
an MRC model when only data from a moderately dense network of rain gauges
is available, rather than from the full rainfall field. The number of gauges
needs only be sufficient to adequately estimate the variance in the ratio of
the rain rate at the rain gauges to the areal average rain rate across the
entire spatial domain. In our example for Warsaw, Poland, we used 25 gauges
over an area of approximately 1600 km2. MRC models calibrated using
the proposed method were used to downscale 15-min rainfall rates from a
20 by 20 km area to the scale of the rain gauge capture area. Frequency
distributions of observed and simulated 15-min rainfall at the gauge
scale were very similar. Moreover, the spatial covariance structure of
rainfall rates, as characterized by the semivariogram, was reproduced after
allowing the probability density function of the random cascade generator to
vary with spatial scale. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|