Jhon E. Hinestroza-Ramirez, Juan Ernesto Soto Barbosa, Andrés Yarce Botero, Danilo Andrés Suárez Higuita, Santiago Lopez-Restrepo, Lisseth Milena Cruz Ruiz, Valeria Sólorzano Araque, Andres Céspedes, Sara Lorduy Hernandez, Richard Caceres, Giovanni Jiménez‐Sánchez, O. Quintero
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引用次数: 0
Abstract
This manuscript introduces an exploratory case study of the SIMFAC’s (Sistema de Información Meteorológica de la Fuerza Aérea Colombiana) operational implementation of the Weather Research and Forecasting (WRF) model with a 3DVAR (three-dimensional variational) data assimilation scheme that provides meteorological information for military, public, and private aviation. In particular, it investigates whether the assimilation scheme in SIMFAC’s implementation improves the prediction of the variables of interest compared to the implementation without data assimilation (CTRL). Consequently, this study compares SIMFAC’S 3DVAR-WRF operational implementation in Colombia with a CTRL with the same parameterization (without 3DVAR assimilation) against the ground and satellite observations in two operational forecast windows. The simulations are as long as an operational run, and the evaluation is performed using the root mean square error, the mean fractional bias, the percent bias, the correlation factor, and metrics based on contingency tables. It also evaluates the model’s results according to the regions of Colombia, accounting for the country’s topographical differences. The findings reveal that, in general, the operational forecast (3DVAR) is similar to the CTRL without data assimilation, indicating the need for further improvement of the 3DVAR-WRF implementation.
本文介绍了SIMFAC(Sistema de Información Meteorológica de la Fuerza Aérea Colombiana)利用3DVAR(三维变分)数据同化方案实施天气研究和预测(WRF)模型的探索性案例研究,该方案为军事、公共和私人航空提供气象信息。特别是,它调查了与没有数据同化(CTRL)的实施相比,SIMFAC实施中的同化方案是否改进了对感兴趣变量的预测。因此,本研究将SIMFAC在哥伦比亚的3DVAR-WRF操作实施与具有相同参数化(没有3DVAR同化)的CTRL在两个操作预测窗口中的地面和卫星观测进行了比较。模拟与操作运行一样长,使用均方根误差、平均分数偏差、百分比偏差、相关系数和基于列联表的指标进行评估。它还根据哥伦比亚的地区评估了该模型的结果,考虑到该国的地形差异。研究结果表明,总体而言,在没有数据同化的情况下,作战预测(3DVAR)与CTRL相似,这表明需要进一步改进3DVAR-WRF的实施。
ClimateEarth and Planetary Sciences-Atmospheric Science
CiteScore
5.50
自引率
5.40%
发文量
172
审稿时长
11 weeks
期刊介绍:
Climate is an independent, international and multi-disciplinary open access journal focusing on climate processes of the earth, covering all scales and involving modelling and observation methods. The scope of Climate includes: Global climate Regional climate Urban climate Multiscale climate Polar climate Tropical climate Climate downscaling Climate process and sensitivity studies Climate dynamics Climate variability (Interseasonal, interannual to decadal) Feedbacks between local, regional, and global climate change Anthropogenic climate change Climate and monsoon Cloud and precipitation predictions Past, present, and projected climate change Hydroclimate.