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Convective rain cell characteristics and scaling in climate projections for Germany
International Journal of Climatology ( IF 3.5 ) Pub Date : 2021-01-15 , DOI: 10.1002/joc.7012
Christopher Purr 1 , Erwan Brisson 1, 2 , Bodo Ahrens 1
Affiliation  

Extreme convective precipitation is expected to increase with global warming. However, the rate of increase and the understanding of contributing processes remain highly uncertain. We investigated characteristics of convective rain cells like area, intensity, and lifetime as simulated by a convection‐permitting climate model in the area of Germany under historical (1976–2005) and future (end‐of‐century, RCP8.5 scenario) conditions. To this end, a tracking algorithm was applied to 5‐min precipitation output. While the number of convective cells is virtually similar under historical and future conditions, there are more intense and larger cells in the future. This yields an increase in hourly precipitation extremes, although mean precipitation decreases. The relative change in the frequency distributions of area, intensity, and precipitation sum per cell is highest for the most extreme percentiles, suggesting that extreme events intensify the most. Furthermore, we investigated the temperature and moisture scaling of cell characteristics. The temperature scaling drops off at high temperatures, with a shift in drop‐off towards higher temperatures in the future, allowing for higher peak values. In contrast, dew point temperature scaling shows consistent rates across the whole dew point range. Cell characteristics scale at varying rates, either below (mean intensity), at about (maximum intensity and area), or above (precipitation sum) the Clausius–Clapeyron rate. Thus, the widely investigated extreme precipitation scaling at fixed locations is a complex product of the scaling of different cell characteristics. The dew point scaling rates and absolute values of the scaling curves in historical and future conditions are closest for the highest percentiles. Therefore, near‐surface humidity provides a good predictor for the upper limit of for example, maximum intensity and total precipitation of individual convective cells. However, the frequency distribution of the number of cells depending on dew point temperature changes in the future, preventing statistical inference of extreme precipitation from near‐surface humidity.

中文翻译:

对流雨单元的特征和德国气候预测中的尺度变化

随着全球变暖,极端对流降水预计将增加。但是,增长率和对贡献过程的理解仍然非常不确定。我们根据历史(1976–2005)和未来(世纪末,RCP8.5情景)条件下的德国对流允许气候模型,研究了对流雨单元的特征,如面积,强度和寿命。为此,将跟踪算法应用于5分钟的降水量输出。虽然在历史和未来条件下对流细胞的数量实际上是相似的,但未来将有更密集,更大的细胞。尽管平均降水量减少,但这会增加每小时的极端降水量。面积,强度,对于最极端的百分位数,每个单元的降水总和最高,这表明极端事件的加剧最大。此外,我们研究了细胞特性的温度和湿度结垢。温度标度在高温下会下降,将来会下降到更高的温度,从而允许更高的峰值。相反,露点温度定标在整个露点范围内显示出一致的速率。细胞特征以不同的速率缩放,或者低于(平均强度),大约(最大强度和面积),或者高于(降水量)克劳修斯-克拉珀龙速率。因此,广泛研究的在固定位置的极端降水结垢是不同细胞特征的结垢的复杂产物。对于最高百分位数,历史和未来条件下的露点缩放比例和缩放比例曲线的绝对值最接近。因此,近地表湿度可以很好地预测单个对流细胞的上限,例如最大强度和总降水量。但是,电池数目的频率分布取决于将来的露点温度变化,从而防止了从表面湿度引起的极端降水的统计推断。
更新日期:2021-01-15
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