Details zur Publikation

Kategorie Textpublikation
Referenztyp Zeitschriften
DOI 10.1002/2014WR015930
Titel (primär) Stochastic temporal disaggregation of monthly precipitation for regional gridded data sets
Autor Thober, S.; Mai, J.; Zink, M.; Samaniego, L. ORCID logo
Quelle Water Resources Research
Erscheinungsjahr 2014
Department CHS
Band/Volume 50
Heft 11
Seite von 8714
Seite bis 8735
Sprache englisch
Keywords precipitation; downscaling; weather generator; covariance matrix; sequential Gaussian sampling; multiplicative cascade
UFZ Querschnittsthemen RU5;
Abstract Weather generators are used for spatio-temporal downscaling of climate model outputs (e.g., precipitation and temperature) to investigate the impact of climate change on the hydrological cycle. In this study, a multiplicative random cascade model is proposed for the stochastic temporal disaggregation of monthly to daily precipitation fields, which is designed to be applicable to grids of any spatial resolution and extent. The proposed method uses stationary distribution functions that describe the partitioning of precipitation throughout multiple temporal scales (e.g., weekly and bi-weekly scale). Moreover, it explicitly considers the intensity and spatial covariance of precipitation in the disaggregation procedure, but requires no assumption about the temporal relationship and spatial isotropy of precipitation fields. A split sampling test is conducted on a high-resolution (i.e., 4×4 km2 grid) daily precipitation data set over Germany (≈ 357 000 km2) to assess the performance of the proposed method during future periods. The proposed method has proven to consistently reproduce distinctive location dependent precipitation distribution functions with biases less than 5% during both a calibration and evaluation period. Furthermore, extreme precipitation amounts and the spatial and temporal covariance of the generated fields are comparable to those of the observations. Consequently, the proposed temporal disaggregation approach satisfies the minimum conditions for a precipitation generator aiming at the assessment of hydrological response to climate change at regional and continental scales or for generating seamless predictions of hydrological variables.
dauerhafte UFZ-Verlinkung https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=15364
Thober, S., Mai, J., Zink, M., Samaniego, L. (2014):
Stochastic temporal disaggregation of monthly precipitation for regional gridded data sets
Water Resour. Res. 50 (11), 8714 - 8735 10.1002/2014WR015930