Journal of Earth System Science ( IF 1.9 ) Pub Date : 2021-04-09 , DOI: 10.1007/s12040-021-01556-8 S M Kirthiga , B Narasimhan , C Balaji
Abstract
The southern peninsular India is characterized by unique climatology with rainfall processes throughout the year from land–ocean contrasts. In addition, the complex terrain induces localized effects causing huge spatial and temporal variability in the observed precipitation. This study aims at evaluating the sensitivity of the high-resolution Weather Research and Forecasting (WRF) model (4 km) to multi-physics parameterizations, 3D variational data assimilation, and domain configuration, in the study domain covering southern peninsular India. Furthermore, the study focusses on the formulation of an ensemble method to improve the simulation of precipitation across seasons. A total of 120 experiments were set up across four crucial rainfall events, of varying spatial extent and duration, dominated by different rainfall generation mechanisms. The assessment of the experiments shows that the model’s cumulus and microphysics schemes have the highest impact on the location, intensity, and spread of the simulated 4-day long Quantitative Precipitation Forecasts (QPFs). Applying cumulus schemes at all domains represented the variability in the QPFs, across space and time, for the precipitation events dominated by convective activity. The cases without cumulus schemes at the convective scale domain (4 km), captured the higher intensity rains during organized cyclonic circulations in the north-east monsoon period. Hence, a 10-member multi-physics ensemble approach including members with and without cumulus parameterization at the fine resolution domain was adopted. The preliminary results demonstrate that the mean from the suggested ensemble approach (n-MPP) performed well in capturing the dynamics of QPFs across the rainfall events, as opposed to a single-member deterministic simulation and mean from larger member conventional multi-physics ensemble approach (c-MPP) without cumulus parameterization at the convective scale. The rank histogram, delta semi-variance plots, and outlier statistics at various lead times clearly showed that the suggested n-MPP was able to capture the high-intensity rainfall, increasing the spread of precipitation forecasts and consequently reducing the occurrence of outliers.
Highlights
-
Evaluated the sensitivity of a high-resolution Numerical Weather Prediction (NWP) model (4 km) with 120 experiments in generating short-term (4-day long) quantitative precipitation forecasts (QPFs).
-
The cumulus and microphysics schemes have the highest impact on the location, intensity, and spread of the simulated rainfall across events dominated by different rainfall generation mechanisms.
-
A 10-member multi-physics ensemble approach including members with and without cumulus parameterization at the fine resolution domain was able to capture the high-intensity rainfall, increasing the spread of precipitation forecasts and consequently reducing the occurrence of outliers.
中文翻译：
基于对流半岛南部地区敏感性实验的对流许可尺度下多物理场综合预报方法
摘要
印度南部半岛的特点是独特的气候学，全年从陆海对比来看降雨过程。此外，复杂的地形会诱发局部效应，从而在观测到的降水中造成巨大的时空变化。这项研究旨在评估高分辨率天气研究与预报（WRF）模型（4公里）在涵盖印度南部半岛的研究领域中对多物理场参数化，3D变异数据同化和域配置的敏感性。此外，研究集中在整体方法的制定上，以改善整个季节降水的模拟。在四个关键的降雨事件中建立了总共120个实验，这些事件具有不同的空间范围和持续时间，主要受不同的降雨产生机制控制。实验评估表明，该模型的积云和微观物理方案对模拟的4天定量降水预报（QPF）的位置，强度和传播影响最大。在对流活动占主导的降水事件中，在所有领域都采用积云方案表示了QPF在空间和时间上的变异性。在对流尺度域（4 km）没有积云方案的情况下，在东北季风时期有组织的气旋环流期间捕获了较高强度的降雨。因此，采用了由十个成员组成的多物理场集成方法，该方法包括在高分辨率域上具有和不具有累积参数化的成员。初步结果表明，与单成员确定性模拟和较大成员的常规多物理集合方法相比，建议的集合方法（n-MPP）的平均值在捕获整个降雨事件中的QPF动态方面表现良好。 （c-MPP），在对流尺度上不进行累积参数设置。等级直方图，δ半方差图和各种提前期的离群值统计清楚地表明，建议的n-MPP能够捕获高强度降雨，增加了降水预报的散布范围，因此减少了离群值的发生。与单成员确定性仿真相反，而对流尺度上没有累积参数化的情况下，则采用较大成员的常规多物理集合方法（c-MPP）进行均值计算。等级直方图，δ半方差图和各种提前期的离群值统计清楚地表明，建议的n-MPP能够捕获高强度降雨，增加了降水预报的散布范围，因此减少了离群值的发生。与单成员确定性仿真相反，而对流尺度上没有累积参数化的情况下，则采用较大成员的常规多物理集合方法（c-MPP）进行均值计算。等级直方图，δ半方差图和各种提前期的离群值统计清楚地表明，建议的n-MPP能够捕获高强度降雨，增加了降水预报的散布范围，因此减少了离群值的发生。
强调
-
通过120个实验来评估短期（4天长）定量降水预报（QPF），评估了高分辨率数值天气预报（NWP）模型（4 km）的敏感性。
-
积云和微物理方案对模拟降雨的位置，强度和跨受不同降雨产生机制支配的事件的分布的影响最大。
-
一个由10个成员组成的多物理场集成方法，包括在高分辨率域上具有和不具有累积参数设置的成员，都可以捕获高强度降雨，从而增加了降水预报的传播范围，因此减少了异常值的发生。
京公网安备 11010802027423号