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Environmental Lapse Rate for High‐Resolution Land Surface Downscaling: An Application to ERA5

机译:高分辨率落地场的环境流逝速度下降:在ERA5应用

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In this study we derive the environmental lapse rate (ELR) from vertical profiles of temperature in the lower troposphere, applying it to downscale air temperature of the new European Centre For Medium‐Range Weather Forecasts (ECMWF) reanalysis ERA5, which replaces ERA‐Interim (ERAI). We focus over the western U.S. region, a data‐rich area with observations of daily maximum and minimum temperature (Global Historical Climatology Network) and snow depth and soil temperature. Observations indicate an ELR of ?4.5?K·km?1 in the region, lower than the commonly used ?6.5?K·km?1. ERA5 ELR agrees with the observational estimates, with some overestimation in winter and limitations in the diurnal variability. The elevation correction of ERA5 temperature using different ELR showed the benefits of deriving ELR fields from ERA5 vertical profiles, when compared with a constant ELR. Simulations with the ECMWF land surface model, at 9‐km resolution, driven by ERA5 using different ELR corrections showed the added value of the methodology, but the impact of different ELR corrections is limited. However, the validity of the downscaling method in reducing temperature to station altitude suggests that there is sufficient generality for application at kilometer and subkilometer resolutions. By comparing the estimated representativity errors of observations with reanalysis, the improvements from ERAI to ERA5 are mainly visible in the random component of the error. Large systematic biases remain, which require further attention from the modeling and data assimilation, and limit the potential benefits of ELR corrections.
机译:在这项研究中,我们从较低对流层中的温度垂直型材(ELR)导出了环境流逝速率(ELR),将其应用于新的欧洲中距离(ECMWF)Reanalysics Era5的新欧洲中级天气预报中心的低档空气温度,这取代了Era-Instim (Erai)。我们专注于美国地区,具有日常最大和最低温度(全球历史气候网络)和雪深和土壤温度的数据富裕地区。观察结果表明了该地区的4.5?k·km?1,低于常用的?6.5?k·km?1。 ERA5 ELR同意观察估计数,在冬季和昼夜变异性中的局限性估计。使用不同ELR的ERA5温度的高度校正显示,与恒定的ELR相比,从ERA5垂直轮廓中衍生ELR场的益处。通过ERA5使用不同的ELR校正驱动的9公里分辨率的仿真与9公里的分辨率显示了方法的附加值,但不同的ELR校正的影响是有限的。然而,在将温度降低到站海拔地区的缩小装置的有效性表明,在公里和子千克分辨率下施加足够的普遍性。通过比较再分析的观察结果的估计代表性误差,Erai至Era5的改进主要在误差的随机成分中可见。留下大量系统偏差,需要进一步关注建模和数据同化,并限制ELR校正的潜在益处。

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