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Sub-kilometer dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models

机译:使用WRF和MM5中尺度模型在复杂地形中对近地表风进行亚公里动态降尺度

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Sub-kilometer dynamical downscaling was performed using the Weather Research and Forecasting (WRF) and Mesoscale Model Version 5 (MM5) models. The models were configured with horizontal grid spacing ranging from 27 km in the outermost telescoping to 333 m in the innermost domains and verified with observations collected at four 50-m towers in west-central Nevada during July and December 2007. Moment-based and spectral verification metrics showed that the performance of WRF was superior to MM5. The modeling results were more accurate at 50 m than at 10 m AGL. Both models accurately simulated the mean near-surface wind shear; however, WRF (MM5) generally overestimated (underestimated) mean wind speeds at these levels. The dispersion errors were the dominant component of the root-mean square errors. The major weakness of WRF was the overestimation of the intensity and frequency of strong nocturnal thermally driven flows and their sub-diurnal scale variability, while the main weaknesses of MM5 were larger biases, underestimation of the frequency of stronger daytime winds in the mixed layer and underestimation of the observed spectral kinetic energy of the major energy-containing motions. Neither of the verification metrics showed systematic improvement in the models' accuracy with increasing the horizontal resolution and the share of dispersion errors increased with increased resolution. However, a profound improvement in the moment-based accuracy was found for the mean vertical wind shear and the temporal variability of wind speed, in particular for summer daytime simulations of the thermally driven flows. The most prominent spectral accuracy improvement among the primary energy-containing frequency bands was found for both models in the summertime diurnal periods. Also, the improvement for WRF (MM5) was more (less) apparent for longer-than-diurnal than for sub-diurnal periods. Finally, the study shows that at least near-kilometer horizontal grid spacing is necessary for dynamical downscaling of near-surface wind speed climate over complex terrain; however, some of the physics options might be less appropriate for grid spacing nearing the scales of the energy-containing turbulent eddies, i.e., resolutions of several hundred meters. In addition to the effects of the lower boundary, the accuracy of the lateral boundary conditions of the parent domains also controls the onset and evolution of the thermally driven flows.
机译:使用“天气研究与预报(WRF)”和“中尺度模型版本5(MM5)”模型执行亚公里动态降尺度。这些模型配置了水平网格间距,范围从最外层的27 km到最内层的333 m,并通过内华达州中西部的四座50 m塔在2007年7月和2007年12月收集的观测结果进行了验证。基于矩和频谱验证指标表明,WRF的性能优于MM5。在50 m时的建模结果比在10 m AGL时更准确。两种模型都精确模拟了近地表风的平均切变。但是,WRF(MM5)通常被高估(低估)了这些水平的平均风速。色散误差是均方根误差的主要成分。 WRF的主要弱点是高估了强夜热驱动气流的强度和频率,以及它们的亚昼间尺度变化,而MM5的主要弱点是较大的偏差,低估了混合层中日风的频率。低估了包含主要能量运动的频谱动能。两种验证指标均未显示出模型的准确性随水平分辨率的提高而得到系统性改善,色散误差的份额随分辨率的提高而增加。但是,对于平均垂直风切变和风速的时间变化,发现基于矩的精度有了很大的提高,尤其是在夏季白天对热驱动流的​​模拟中。在夏季的白天,两个模型都在包含主要能量的频带中发现了最显着的频谱准确性改善。同样,与昼夜相比,昼夜更长的WRF(MM5)的改善更为明显。最后,研究表明,对于复杂地形上近地表风速气候的动态缩减,至少需要近千米的水平网格间距;但是,某些物理选择可能不太适合网格间距接近包含能量的湍流涡旋尺度,即几百米的分辨率。除了下边界的影响之外,父域的横向边界条件的准确性还控制了热驱动流的​​发生和演化。

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