edu.ucar.opensky::articles:18040 UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact 2025-12-26T02:55:39.489766 ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data ISO 19115-2:2009(E) https://n2t.org/ark:/85065/d7br8tq6 Statistical downscaling of seasonal precipitation in Israel 2016-02-01T00:00:00Z publication https://n2t.org/ark:/85065/d7br8tq6 https://doi.org/10.1002/joc.4368 Rostkier-Edelstein, D. author Kunin, P. author Hopson, Thomas M. author Liu, Yubao author Givati, A. author UCAR/NCAR - Library publisher Careful planning of the use of water resources is critical in the semi-arid eastern Mediterranean region. The relevant areas are characterized by complex terrain and coastlines, and exhibit large spatial variability in seasonal precipitation. Global seasonal forecasts provide only partial information of the precipitation as a result of their coarse spatial resolution. We present two statistical downscaling methods of global forecasts, both identifying past-analogue synoptic-weather patterns and their connection to precipitation at specific stations. The first method utilizes a classification of the large-scale weather patterns into regimes, and the other identifies the closest past analogues directly without grouping the weather events. The validation of the algorithms using NCEP/NCAR reanalyses and past precipitation observations at 18 stations shows that both methods provide good skill in predicting mean precipitation amounts and quantiles of the precipitation distribution, and in reproducing the observed inter-annual and spatial variability. Both methods show good correlations between predicted and observed precipitation amounts (∼0.8), and the downscaled precipitation reproduces the observed differences between the stations, which are not available in the coarse global models. Based on these results, we downscaled the operational global-seasonal forecasts issued by the NCEP CFS1.0 ensemble. This approach could also have utility in climate change scenario downscaling. UCAR/NCAR - Library OpenSky Support PO Box 3000 Boulder CO 80307-3000 opensky@ucar.edu http://opensky.ucar.edu/ homepage pointOfContact PDF Text theme Resource Type 2016-01-01T00:00:00Z publication Copyright 2016 Royal Meteorological Society. None eng geoscientificInformation