scholarly journals The Weather Research and Forecasting (WRF) model contribution to the atmospheric conditions estimation during the EUSO-Balloo

2016 ◽  
Author(s):  
Ilaria Tabone ◽  
Mario E. Bertaina
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Weather Research

Predicting lightning activity in Greece with the Weather Research and Forecasting (WRF) model

2015 ◽  
Vol 156 ◽  
pp. 1-13 ◽  
Author(s):  
Theodore M. Giannaros ◽  
Vassiliki Kotroni ◽  
Konstantinos Lagouvardos
Keyword(s):  
Wrf Model ◽  
Lightning Activity ◽  
Weather Research And Forecasting ◽  
Weather Research

scholarly journals A new moisture tagging capability in the Weather Research and Forecasting Model: formulation, validation and application to the 2014 Great Lake-effect snowstorm

2017 ◽  
Author(s):  
Damián Insua-Costa ◽  
Gonzalo Miguez-Macho
Keyword(s):  
Great Lake ◽  
Snow Water Equivalent ◽  
Precipitable Water ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Meteorological Model ◽  
Moisture Sources ◽  
Lake Effect ◽  
Snow Water ◽  
Weather Research

Abstract. A new moisture-tagging tool, usually known as water vapor tracer (WVT) method or online Eulerian method, has been implemented into the Weather Research and Forecasting (WRF) regional meteorological model, enabling it for precise studies on atmospheric moisture sources and pathways. We present here the method and its formulation, along with details of the implementation into WRF. We perform an in-depth validation with monthly long simulations over North America at 20 km resolution, tagging all possible moisture sources: lateral boundaries, continental, maritime or lake surfaces and initial atmospheric conditions. We estimate errors as the moisture or precipitation amounts that cannot be traced back to any source. Validation results indicate that the method exhibits high precision, with errors considerably lower than 1 % during the entire simulation period, for both precipitation and total precipitable water. We apply the method to the Great Lake-effect snowstorm of November 2014, aiming at quantifying the contribution of lake evaporation to the large snow accumulations observed in the event. We perform simulations in a nested domain at 5 km resolution with the tagging technique, demonstrating that about 30–50 % of precipitation in the regions immediately downwind, originated from evaporated moisture in the Great Lakes. This contribution increases to between 50–60 % of the snow water equivalent in the most severely affected areas, which suggests that evaporative fluxes from the lakes have a fundamental role in producing the most extreme accumulations in these episodes, resulting in the highest socio-economic impacts.

scholarly journals Simulation of Severe Thunderstorms in Conjugation of Westerly and Easterly on 31 March 2019 in Bangladesh

2022 ◽  
Vol 12 (3) ◽  
pp. 29-43
Author(s):  
Samarendra Karmakar ◽  
Mohan Kumar Das ◽  
Md Quamrul Hassam ◽  
Md Abdul Mannan
Keyword(s):  
South Asian ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Weather Research And Forecasting ◽  
Atmospheric Conditions ◽  
Microphysics Scheme ◽  
Severe Thunderstorms ◽  
Synoptic Conditions ◽  
Pbl Scheme ◽  
Single Moment

The diagnostic and prognostic studies of thunderstorms/squalls are very important to save live and loss of properties. The present study aims at diagnose the different tropospheric parameters, instability and synoptic conditions associated the severe thunderstorms with squalls, which occurred at different places in Bangladesh on 31 March 2019. For prognostic purposes, the severe thunderstorms occurred on 31 March 2019 have been numerically simulated. In this regard, the Weather Research and Forecasting (WRF) model is used to predict different atmospheric conditions associated with the severe storms. The study domain is selected for 9 km horizontal resolution, which almost covers the south Asian region. Numerical experiments have been conducted with the combination of WRF single-moment 6 class (WSM6) microphysics scheme with Yonsei University (YSU) PBL scheme in simulation of the squall events. Model simulated results are compared with the available observations. The observed values of CAPE at Kolkata both at 0000 and 1200 UTC were 2680.4 and 3039.9 J kg-1 respectively on 31 March 2019 and are found to be comparable with the simulated values. The area averaged actual rainfall for 24 hrs is found is 22.4 mm, which complies with the simulated rainfall of 20-25 mm for 24 hrs. Journal of Engineering Science 12(3), 2021, 29-43

scholarly journals CORDEX-WRF v1.3: development of a module for the Weather Research and Forecasting (WRF) model to support the CORDEX community

2019 ◽  
Vol 12 (3) ◽  
pp. 1029-1066 ◽  
Author(s):  
Lluís Fita ◽  
Jan Polcher ◽  
Theodore M. Giannaros ◽  
Torge Lorenz ◽  
Josipa Milovac ◽  
...  
Keyword(s):  
Regional Climate ◽  
Regional Scale ◽  
Wrf Model ◽  
Data Access ◽  
Quality Data ◽  
Weather Research And Forecasting ◽  
Time Step ◽  
Mitigation And Adaptation ◽  
Data Requirements ◽  
Weather Research

Abstract. The Coordinated Regional Climate Downscaling Experiment (CORDEX) is a scientific effort of the World Climate Research Program (WRCP) for the coordination of regional climate initiatives. In order to accept an experiment, CORDEX provides experiment guidelines, specifications of regional domains, and data access and archiving. CORDEX experiments are important to study climate at the regional scale, and at the same time, they also have a very prominent role in providing regional climate data of high quality. Data requirements are intended to cover all the possible needs of stakeholders and scientists working on climate change mitigation and adaptation policies in various scientific communities. The required data and diagnostics are grouped into different levels of frequency and priority, and some of them even have to be provided as statistics (minimum, maximum, mean) over different time periods. Most commonly, scientists need to post-process the raw output of regional climate models, since the latter was not originally designed to meet the specific CORDEX data requirements. This post-processing procedure includes the computation of diagnostics, statistics, and final homogenization of the data, which is often computationally costly and time-consuming. Therefore, the development of specialized software and/or code is required. The current paper presents the development of a specialized module (version 1.3) for the Weather Research and Forecasting (WRF) model capable of outputting the required CORDEX variables. Additional diagnostic variables not required by CORDEX, but of potential interest to the regional climate modeling community, are also included in the module. “Generic” definitions of variables are adopted in order to overcome the model and/or physics parameterization dependence of certain diagnostics and variables, thus facilitating a robust comparison among simulations. The module is computationally optimized, and the output is divided into different priority levels following CORDEX specifications (Core, Tier 1, and additional) by selecting pre-compilation flags. This implementation of the module does not add a significant extra cost when running the model; for example, the addition of the Core variables slows the model time step by less than a 5 %. The use of the module reduces the requirements of disk storage by about a 50 %. The module performs neither additional statistics over different periods of time nor homogenization of the output data.

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