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- Title
Probabilistic downscaling of precipitation data in a subtropical mountain area: a two-step approach.
- Authors
Haas, R.; Born, K.
- Abstract
In this study, a two-step probabilistic downscaling approach is introduced and evaluated. The method is exemplarily applied on precipitation observations in the subtropical mountain environment of the High Atlas in Morocco. The challenge is to deal with a complex terrain, heavily skewed precipitation distributions and a sparse amount of data, both spatial and temporal. In the first step of the approach, a transfer function between distributions of large-scale predictors and of local observations is derived. The aim is to forecast cumulative distribution functions with parameters from known data. In order to interpolate between sites, the second step applies multiple linear regression on distribution parameters of observed data using local topographic information. By combining both steps, a prediction at every point of the investigation area is achieved. Both steps and their combination are assessed by cross-validation and by splitting the available dataset into a trainings- and a validation-subset. Due to the estimated quantiles and probabilities of zero daily precipitation, this approach is found to be adequate for application even in areas with difficult topographic circumstances and low data availability.
- Subjects
HIGH Atlas Mountains (Morocco); MOROCCO; TROPICS; METEOROLOGICAL precipitation; PROBABILITY theory; REGRESSION analysis; DATA analysis
- Publication
Nonlinear Processes in Geophysics, 2011, Vol 18, Issue 2, p223
- ISSN
1023-5809
- Publication type
Article
- DOI
10.5194/npg-18-223-2011