Volume 7, Issue 3 (11-2020)                   2020, 7(3): 107-124 | Back to browse issues page

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Jaberi P, Sabetghadam S, Ghader S. Visibility prediction during fog and precipitation using the WRF model over Tehran. Journal title 2020; 7 (3) :107-124
URL: http://jsaeh.khu.ac.ir/article-1-2957-en.html
1- , ssabet@ut.ac.ir
Abstract:   (1703 Views)
Visibility is one of the most important optical characteristics of the atmosphere. Prediction of visibility is essential for air pollution, air traffic, flight safety, road traffic and shipping. Visibility reduction may be caused by different reasons. Fog is one of the most common reasons of visibility reduction, i.e. the droplets of water suspended in the atmosphere reduce the visibility to less than 1 km. Precipitation may also reduce visibility. Prediction of visibility in NWP models is usually accomplished by using the relationship between visibility and liquid water content, temperature, relative humidity. Purpose of the present work is to predict visibility during fog and precipitation over Tehran area in January 11th, 2014 and March 7th, 2013. Different algorithms including UPP1, AFWA, FSL and SW99 have been experimented to predict visibility.. Predicted visibility has been compared to observations, including Synoptic and METAR data in Imam Khomeini and Mehrabad airport.  The  WRF version 3.8.1 has been used to simulate precipitation and fog. In this simulation model configuration defined in Lambert uniform space. The model consist three nested domains. First domain was a 27-km grid model (83×65), surrounding a 9-km grid model (112×94) which was surrounding a 3-km grid model (112×97). Center of all domains was at longitude 51° and 44' and latitude 36° and 5' which is located almost at center of Tehran. All domains had 40 vertical layers and model top was located at 100hPa. The out puts of 3-km domain is used for visibility estimation. Initial and boundary conditions were set by using FNL data which is 1°×1° degree grid data. This data is available every 6 hours. Simulations were in 36 hours and first 12 hours was the spin up time. Results show that most of these algorithms can partly predict visibility reduction. The FSL algorithm works better than the other methods in fog situation and SW99 works better in snow situation. Comparing results shows that the visibility reduction during snow is more reliable than during fog. There were some errors in model predictions some of them were due to visibility algorithms, because the coefficients of these algorithms were driven in other parts of earth. The other errors were systematic errors of WRF. Predictions of temperature had warm bias and also there were positive bias in prediction of relative humidity.  
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Type of Study: Research | Subject: Special
Received: 2019/05/1 | Accepted: 2020/02/16 | Published: 2021/02/20

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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