| contributor author | Gianotti, Dan | |
| contributor author | Anderson, Bruce T. | |
| contributor author | Salvucci, Guido D. | |
| date accessioned | 2017-06-09T17:07:46Z | |
| date available | 2017-06-09T17:07:46Z | |
| date copyright | 2013/08/01 | |
| date issued | 2013 | |
| identifier issn | 0894-8755 | |
| identifier other | ams-79822.pdf | |
| identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4222645 | |
| description abstract | generalizable method is presented for establishing the potential predictability for seasonal precipitation occurrence using rain gauge data. This method provides an observationally based upper limit for potential predictability for 774 weather stations in the contiguous United States. It is found that the potentially predictable fraction varies seasonally and spatially, and that on average 30% of year-to-year seasonal variability is potentially explained by predictable climate processes. Potential predictability is generally highest in winter, appears to be enhanced by orography and land surface coupling, and is lowest (stochastic variance is highest) along the Pacific coast. These results depict ?hot? spots of climate variability, for use in guiding regional climate forecasting and in uncovering processes driving climate. Identified ?cold? spots are equally useful in guiding future studies as predictable climate signals in these areas will likely be undetectable. | |
| publisher | American Meteorological Society | |
| title | What Do Rain Gauges Tell Us about the Limits of Precipitation Predictability? | |
| type | Journal Paper | |
| journal volume | 26 | |
| journal issue | 15 | |
| journal title | Journal of Climate | |
| identifier doi | 10.1175/JCLI-D-12-00718.1 | |
| journal fristpage | 5682 | |
| journal lastpage | 5688 | |
| tree | Journal of Climate:;2013:;volume( 026 ):;issue: 015 | |
| contenttype | Fulltext | |