Spread and Skill in Mixed- and Single-Physics Convection-Allowing EnsemblesSource: Weather and Forecasting:;2018:;volume 034:;issue 002::page 305DOI: 10.1175/WAF-D-18-0078.1Publisher: American Meteorological Society
Abstract: AbstractSpread and skill of mixed- and single-physics convection-allowing ensemble forecasts that share the same set of perturbed initial and lateral boundary conditions are investigated at a variety of spatial scales. Forecast spread is assessed for 2-m temperature, 2-m dewpoint, 500-hPa geopotential height, and hourly accumulated precipitation both before and after a bias-correction procedure is applied. Time series indicate that the mixed-physics ensemble forecasts generally have greater variance than comparable single-physics forecasts. While the differences tend to be small, they are greatest at the smallest spatial scales and when the ensembles are not calibrated for bias. Although differences between the mixed- and single-physics ensemble variances are smaller for the larger spatial scales, variance ratios suggest that the mixed-physics ensemble generates more spread relative to the single-physics ensemble at larger spatial scales. Forecast skill is evaluated for 2-m temperature, dewpoint temperature, and bias-corrected 6-h accumulated precipitation. The mixed-physics ensemble generally has lower 2-m temperature and dewpoint root-mean-square error (RMSE) compared to the single-physics ensemble. However, little difference in skill or reliability is found between the mixed- and single-physics bias-corrected precipitation forecasts. Overall, given that mixed- and single-physics ensembles have similar spread and skill, developers may prefer to implement single- as opposed to mixed-physics convection-allowing ensembles in future operational systems, while accounting for model error using stochastic methods.
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| contributor author | Loken, Eric D. | |
| contributor author | Clark, Adam J. | |
| contributor author | Xue, Ming | |
| contributor author | Kong, Fanyou | |
| date accessioned | 2019-10-05T06:44:20Z | |
| date available | 2019-10-05T06:44:20Z | |
| date copyright | 11/21/2018 12:00:00 AM | |
| date issued | 2018 | |
| identifier other | WAF-D-18-0078.1.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4263269 | |
| description abstract | AbstractSpread and skill of mixed- and single-physics convection-allowing ensemble forecasts that share the same set of perturbed initial and lateral boundary conditions are investigated at a variety of spatial scales. Forecast spread is assessed for 2-m temperature, 2-m dewpoint, 500-hPa geopotential height, and hourly accumulated precipitation both before and after a bias-correction procedure is applied. Time series indicate that the mixed-physics ensemble forecasts generally have greater variance than comparable single-physics forecasts. While the differences tend to be small, they are greatest at the smallest spatial scales and when the ensembles are not calibrated for bias. Although differences between the mixed- and single-physics ensemble variances are smaller for the larger spatial scales, variance ratios suggest that the mixed-physics ensemble generates more spread relative to the single-physics ensemble at larger spatial scales. Forecast skill is evaluated for 2-m temperature, dewpoint temperature, and bias-corrected 6-h accumulated precipitation. The mixed-physics ensemble generally has lower 2-m temperature and dewpoint root-mean-square error (RMSE) compared to the single-physics ensemble. However, little difference in skill or reliability is found between the mixed- and single-physics bias-corrected precipitation forecasts. Overall, given that mixed- and single-physics ensembles have similar spread and skill, developers may prefer to implement single- as opposed to mixed-physics convection-allowing ensembles in future operational systems, while accounting for model error using stochastic methods. | |
| publisher | American Meteorological Society | |
| title | Spread and Skill in Mixed- and Single-Physics Convection-Allowing Ensembles | |
| type | Journal Paper | |
| journal volume | 34 | |
| journal issue | 2 | |
| journal title | Weather and Forecasting | |
| identifier doi | 10.1175/WAF-D-18-0078.1 | |
| journal fristpage | 305 | |
| journal lastpage | 330 | |
| tree | Weather and Forecasting:;2018:;volume 034:;issue 002 | |
| contenttype | Fulltext |