Please be advised that the site will be down for maintenance on Sunday, September 1, 2024, from 08:00 to 18:00, and again on Monday, September 2, 2024, from 08:00 to 09:00. We apologize for any inconvenience this may cause.
dc.contributor.author | Shirvani, Amin![]() |
|
dc.contributor.author | Landman, Willem Adolf![]() |
|
dc.date.accessioned | 2017-05-10T06:49:41Z | |
dc.date.issued | 2016-09 | |
dc.description.abstract | This paper examines the skill of seasonal precipitation forecasts over Iran using one two-tiered model, three National Multi-Model Ensemble (NMME) models, and two coupled ocean–atmosphere or one-tiered models. These models are, respectively, the ECHAM4.5 atmospheric model that is forced with sea surface temperature (SST) anomalies forecasted using constructed analogue SSTs (ECHAM4.5-SSTCA); the IRI-ECHAM4.5-DirectCoupled, the NASA-GMAO-062012 and the NCEP-CFSv2; and the ECHAM4.5 Modular Ocean Model version 3 (ECHAM4.5-MOM3-DC2) and the ECHAM4.5-GML-NCEP Coupled Forecast System (CFSSST). The precipitation and 850 hPa geopotential height fields of the forecast models are statistically downscaling to the 0.5∘ × 0.5∘ spatial resolution of the Global Precipitation Climatology Centre (GPCC) Version 6 gridded precipitation data, using model output statistics (MOS) developed through the canonical correlation analysis (CCA) option of the Climate Predictability Tool (CPT). Retroactive validations for lead times of up to 3 months are performed using the relative operating characteristic (ROC) and reliability diagrams, which are evaluated for above- and below-normal categories and defined by the upper and lower 75th and 25th percentiles of the data record over the 15-year test period of 1995/1996 to 2009/2010. The forecast models’ skills are also compared with skills obtained by (a) downscaling simulations produced by forcing the ECHAM4.5 with simultaneously observed SST, and (b) the 850 hPa geopotential height NCEP-NCAR (National Centers for Environmental Prediction-National Center for Atmospheric Research) reanalysis data. Downscaling forecasts from most models generally produce the highest skill forecast at lead times of up to 3 months for autumn precipitation – the October-November-December (OND) season. For most seasons, a high skill is obtained from ECHAM4.5-MOM3-DC2 forecasts at a 1-month lead time when the models’ 850 hPa geopotential height fields are used as the predictor fields. For this model and lead time, the Pearson correlation between the area-averaged of the observed and forecasts over the study area for the OND, November-December-January (NDJ), December-January-February (DJF) and January-February-March (JFM) seasons were 0.68, 0.62, 0.42 and 0.43, respectively | en_ZA |
dc.description.department | Geography, Geoinformatics and Meteorology | en_ZA |
dc.description.embargo | 2017-09-30 | |
dc.description.librarian | hb2017 | en_ZA |
dc.description.sponsorship | The Fars Regional Water Organization | en_ZA |
dc.description.uri | http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-0088 | en_ZA |
dc.identifier.citation | Shirvani, A & Landman, WA 2016, 'Seasonal precipitation forecast skill over Iran', International Journal of Climatology, vol. 36, no. 4, pp. 1887-1900. | en_ZA |
dc.identifier.issn | 0899-8418 (print) | |
dc.identifier.issn | 1097-0088 (online) | |
dc.identifier.other | 10.1002/joc.4467 | |
dc.identifier.uri | http://hdl.handle.net/2263/60306 | |
dc.language.iso | en | en_ZA |
dc.publisher | Wiley | en_ZA |
dc.rights | © 2015 Royal Meteorological Society. Wiley. This is the pre-peer reviewed version of the following article : Seasonal precipitation forecast skill over Iran,International Journal of Climatology in International Journal of Climatology, vol. 36, no. 4, pp. 1887-1900, 2016. doi : 10.1002/joc.4467. which has been published in final form at : http://onlinelibrary.wiley.comjournal/10.1002/(ISSN)1097-0088. | en_ZA |
dc.subject | Statistical downscaling | en_ZA |
dc.subject | Seasonal forecasting | en_ZA |
dc.subject | Iran | en_ZA |
dc.subject | National multi-model ensemble (NMME) | en_ZA |
dc.subject | Sea surface temperature (SST) | en_ZA |
dc.subject | General circulation model (GCM) | en_ZA |
dc.title | Seasonal precipitation forecast skill over Iran | en_ZA |
dc.type | Postprint Article | en_ZA |