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Evaluation of numerical weather prediction model precipitation forecasts for short-term streamflow forecasting purpose

机译：为短期流量预报目的对数值天气预报模型降水预报的评估

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The quality of precipitation forecasts from four Numerical Weather Prediction (NWP) models is evaluated over the Ovens catchment in Southeast Australia. Precipitation forecasts are compared with observed precipitation at point and catchment scales and at different temporal resolutions. The four models evaluated are the Australian Community Climate Earth-System Simulator (ACCESS) including ACCESS-G with a 80 km resolution, ACCESS-R 37.5 km, ACCESS-A 12 km, and ACCESS-VT 5 km. The skill of the NWP precipitation forecasts varies considerably between rain gauging stations. In general, high spatial resolution (ACCESS-A and ACCESS-VT) and regional (ACCESS-R) NWP models overestimate precipitation in dry, low elevation areas and underestimate in wet, high elevation areas. The global model (ACCESS-G) consistently underestimates the precipitation at all stations and the bias increases with station elevation. The skill varies with forecast lead time and, in general, it decreases with the increasing lead time. When evaluated at finer spatial and temporal resolution (e.g. 5 km, hourly), the precipitation forecasts appear to have very little skill. There is moderate skill at short lead times when the forecasts are averaged up to daily and/or catchment scale. The precipitation forecasts fail to produce a diurnal cycle shown in observed precipitation. Significant sampling uncertainty in the skill scores suggests that more data are required to get a reliable evaluation of the forecasts. The non-smooth decay of skill with forecast lead time can be attributed to diurnal cycle in the observation and sampling uncertainty. Future work is planned to assess the benefits of using the NWP rainfall forecasts for short-term streamflow forecasting. Our findings here suggest that it is necessary to remove the systematic biases in rainfall forecasts, particularly those from low resolution models, before the rainfall forecasts can be used for streamflow forecasting.
机译：在澳大利亚东南部的烤箱集水区，对来自四种数值天气预报（NWP）模型的降水预报质量进行了评估。在点和汇水规模以及不同的时间分辨率下，将降水预报与观测到的降水进行比较。评估的四个模型是澳大利亚社区气候地球系统模拟器（ACCESS），包括分辨率为80 km的ACCESS-G，ACCESS-R 37.5 km，ACCESS-A 12 km和ACCESS-VT 5 km。 NWP降水预报的技巧在测雨站之间存在很大差异。通常，高空间分辨率（ACCESS-A和ACCESS-VT）和区域（ACCESS-R）NWP模型高估了干旱低海拔地区的降水，而低估了潮湿高海拔地区的降水。全球模式（ACCESS-G）始终低估了所有气象站的降水量，并且偏差随着气象站海拔的升高而增加。该技能随预测的交货时间而变化，并且通常，随着交货时间的增加而降低。当以更好的时空分辨率（例如每小时5公里）进行评估时，降水预报似乎技能很少。将预报平均到每日和/或集水规模时，在较短的交付周期内具有中等技能。降水预报未能产生观测到的降水所显示的昼夜周期。技能得分中明显的抽样不确定性表明，需要更多数据才能对预测进行可靠的评估。具有预测提前期的技能的非平稳衰减可以归因于观测和采样不确定性的昼夜周期。计划未来的工作，以评估将NWP降雨预报用于短期流量预报的好处。我们在这里的发现表明，必须先消除降雨预报中的系统偏差，尤其是来自低分辨率模型的偏差，然后才能将降雨预报用于流量预报。

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