Academic literature on the topic 'WRF Modeling'
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Journal articles on the topic "WRF Modeling"
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Mandel, J., J. D. Beezley, and A. K. Kochanski. "Coupled atmosphere-wildland fire modeling with WRF-Fire version 3.3." Geoscientific Model Development Discussions 4, no. 1 (March 9, 2011): 497–545. http://dx.doi.org/10.5194/gmdd-4-497-2011.
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Abstract. We describe the physical model, numerical algorithms, and software structure of WRF-Fire. WRF-Fire consists of a fire-spread model, implemented by the level-set method, coupled with the Weather Research and Forecasting model. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. The level-set method allows submesh representation of the burning region and flexible implementation of various kinds of ignition. WRF-Fire is distributed as a part of WRF and it uses the WRF parallel infrastructure for parallel computing.
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Wang, Jian, Weimin Bao, Qianyu Gao, Wei Si, and Yiqun Sun. "Coupling the Xinanjiang model and wavelet-based random forests method for improved daily streamflow simulation." Journal of Hydroinformatics 23, no. 3 (March 22, 2021): 589–604. http://dx.doi.org/10.2166/hydro.2021.111.
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Abstract Daily streamflow modeling is an important tool for water resources management and flood mitigation. This study compared the performance of the Xinanjiang (XAJ) model and random forests (RF) method in a daily streamflow simulation, and proposed several hybrid models based on the XAJ model, wavelet analysis, and RF method (including XAJ-RF model, WRF model, and XAJ-WRF model). The proposed methods were applied to Shiquan station, located in the Upper Han River basin in China. Five performance measures (NSE, RMSE, PBIAS, MAE, and R) were adopted to evaluate the modeling accuracy. Results showed that XAJ-RF model had a relatively higher level of accuracy than that of the XAJ model and the RF model. Compared to the RF and XAJ-RF models, the performance statistics of WRF and XAJ-WRF were better. The results indicated that the coupled XAJ-RF model can be effectively applied and provide a useful alternative for daily streamflow modeling and the application of wavelet analysis contributed to the increasing accuracy of streamflow modeling. Moreover, 14 wavelet functions from various families were tested to analyze the impact of various mother wavelets on the XAJ-WRF model.
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Pleim, Jonathan E. "Comment on “Simulation of Surface Ozone Pollution in the Central Gulf Coast Region Using WRF/Chem Model: Sensitivity to PBL and Land Surface Physics”." Advances in Meteorology 2011 (2011): 1–3. http://dx.doi.org/10.1155/2011/464753.
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A recently published meteorology and air quality modeling study has several serious deficiencies deserving comment. The study uses the weather research and forecasting/chemistry (WRF/Chem) model to compare and evaluate boundary layer and land surface modeling options. The most serious of the study's deficiencies is reporting WRF/Chem results for both meteorological and chemical quantities using the asymmetric convective model version 2 (ACM2). While the ACM2 is a valid model option for WRF, it has not yet been implemented for the chemical portion of the WRF/Chem model. Hence, the reported air quality modeling results using ACM2 are invalid. Furthermore, publication of these results gives the erroneous impression that the ACM2 model is not well suited for air quality applications when, in fact, it is the default boundary layer model in the community multiscale air quality (CMAQ) model.
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Hammerberg, Kristopher, Milena Vuckovic, and Ardeshir Mahdavi. "Approaches to Urban Weather Modeling: A Vienna Case Study." Applied Mechanics and Materials 887 (January 2019): 344–52. http://dx.doi.org/10.4028/www.scientific.net/amm.887.344.
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Given the adverse implications of both urbanization and global climate change for cities, specifically regarding issues such as human health and comfort, local air quality, and increased summertime energy use in buildings, it is becoming imperative to develop models that can accurately predict the complex and nonlinear interactions between the surrounding urban fabric and local climatic context. Over the past years, a number of comprehensive tools have been widely applied for the generation of near-surface urban climatic information. In this paper, we report on the potential of two alternative approaches to urban climate modeling. Specifically, we compare the climatic output generated with Urban Weather Generator (UWG) and the Weather Research and Forecasting (WRF) model. The WRF model has been widely applied due to its capability of downscaling global weather data to finer resolutions, thus representing the location-specific microclimatic information, while considering the interactions with the surrounding urban and regional context. However, this approach is computationally intensive. The UWG was recently introduced as a simpler alternative to such complex models. The tool morphs rural weather data to represent urban conditions given a set of location-specific morphological parameters. In the present paper, WRF and UWG methods were compared based on empirical data pertaining to air temperature, wind speed, and humidity, collected from 12 locations in the city of Vienna, Austria, over 5 distinct time periods. In general, our results suggest that, as compared to the WRF model, the UWG model results are closer to monitored data. However, during the extreme conditions in summer, the WRF model was found to perform better. It was further noted that the discrepancy between the two models increases with decreasing temperatures, thus revealing a higher offset between UWG and WRF output during the winter period.
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Kochanski, A. K., E. R. Pardyjak, R. Stoll, A. Gowardhan, M. J. Brown, and W. J. Steenburgh. "One-Way Coupling of the WRF–QUIC Urban Dispersion Modeling System." Journal of Applied Meteorology and Climatology 54, no. 10 (October 2015): 2119–39. http://dx.doi.org/10.1175/jamc-d-15-0020.1.
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AbstractSimulations of local weather and air quality in urban areas must account for processes spanning from meso- to microscales, including turbulence and transport within the urban canopy layer. Here, the authors investigate the performance of the building-resolving Quick Urban Industrial Complex (QUIC) Dispersion Modeling System driven with mean wind profiles from the mesoscale Weather Research and Forecasting (WRF) Model. Dispersion simulations are performed for intensive observation periods 2 and 8 of the Joint Urban 2003 field experiment conducted in Oklahoma City, Oklahoma, using an ensemble of expert-derived wind profiles from observational data as well as profiles derived from WRF runs. The results suggest that WRF can be used successfully as a source of inflow boundary conditions for urban simulations, without the collection and processing of intensive field observations needed to produce expert-derived wind profiles. Detailed statistical analysis of tracer concentration fields suggests that, for the purpose of the urban dispersion, WRF simulations provide wind forcing as good as individual or ensemble expert-derived profiles. Despite problems capturing the strength and the elevation of the Great Plains low-level jet, the WRF-simulated near-surface wind speed and direction were close to observations, thus assuring realistic forcing for urban dispersion estimates. Tests performed with multilayer and bulk urban parameterizations embedded in WRF did not provide any conclusive evidence of the superiority of one scheme over the other, although the dispersion simulations driven by the latter showed slightly better results.
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Mandel, J., J. D. Beezley, and A. K. Kochanski. "Coupled atmosphere-wildland fire modeling with WRF 3.3 and SFIRE 2011." Geoscientific Model Development 4, no. 3 (July 7, 2011): 591–610. http://dx.doi.org/10.5194/gmd-4-591-2011.
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Abstract. We describe the physical model, numerical algorithms, and software structure of a model consisting of the Weather Research and Forecasting (WRF) model, coupled with the fire-spread model (SFIRE) module. In every time step, the fire model inputs the surface wind, which drives the fire, and outputs the heat flux from the fire into the atmosphere, which in turn influences the atmosphere. SFIRE is implemented by the level set method, which allows a submesh representation of the burning region and a flexible implementation of various kinds of ignition. The coupled model is capable of running on a cluster faster than real time even with fine resolution in dekameters. It is available as a part of the Open Wildland Fire Modeling (OpenWFM) environment at http://openwfm.org, which contains also utilities for visualization, diagnostics, and data processing, including an extended version of the WRF Preprocessing System (WPS). The SFIRE code with a subset of the features is distributed with WRF 3.3 as WRF-Fire.
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Wang, Wei, Jia Liu, Chuanzhe Li, Yuchen Liu, Fuliang Yu, and Entao Yu. "An Evaluation Study of the Fully Coupled WRF/WRF-Hydro Modeling System for Simulation of Storm Events with Different Rainfall Evenness in Space and Time." Water 12, no. 4 (April 24, 2020): 1209. http://dx.doi.org/10.3390/w12041209.
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With the aim of improving the understanding of water exchanges in medium-scale catchments of northern China, the spatiotemporal characteristics of rainfall and several key water cycle elements e.g., soil moisture, evapotranspiration and generated runoff, were investigated using a fully coupled atmospheric-hydrologic modeling system by integrating the Weather Research and Forecasting model (WRF) and its terrestrial hydrologic component WRF-Hydro (referred to as the fully coupled WRF/WRF-Hydro). The stand-alone WRF model (referred to as WRF-only) is also used as a comparison with the fully coupled system, which was expected to produce more realistic simulations, especially rainfall, by allowing the redistribution of surface and subsurface water across the land surface. Six storm events were sorted by different spatial and temporal distribution types, and categorical and continuous indices were used to distinguish the applicability in space and time between WRF-only and the fully coupled WRF/WRF-Hydro. The temporal indices showed that the coupled WRF-Hydro could improve the time homogeneous precipitation, but for the time inhomogeneous precipitation, it might produce a larger false alarm than WRF-only, especially for the flash storm that occurred in July, 2012. The spatial indices showed a lower mean bias error in the coupled system, and presented an enhanced simulation of both space homogeneous and inhomogeneous storm events than WRF-only. In comparison with WRF-only, the fully coupled WRF/WRF-Hydro had a closer to the observations particularly in and around the storm centers. The redistributions fluctuation of spatial precipitation in the fully coupled system was highly correlated with soil moisture, and a low initial soil moisture could lead to a large spatial fluctuated range. Generally, the fully coupled system produced slightly less runoff than WRF-only, but more frequent infiltration and larger soil moisture. While terrestrial hydrologic elements differed with relatively small amounts in the average of the two catchments between WRF-only and the fully coupled WRF/WRF-Hydro, the spatial distribution of elements in the water cycle before and after coupling with WRF-Hydro was not consistent. The soil moisture, runoff and precipitation in the fully coupled system had a similar spatial trend, but evapotranspiration did not always display the same.
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Eidhammer, Trude, Adam Booth, Sven Decker, Lu Li, Michael Barlage, David Gochis, Roy Rasmussen, Kjetil Melvold, Atle Nesje, and Stefan Sobolowski. "Mass balance and hydrological modeling of the Hardangerjøkulen ice cap in south-central Norway." Hydrology and Earth System Sciences 25, no. 8 (August 3, 2021): 4275–97. http://dx.doi.org/10.5194/hess-25-4275-2021.
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Abstract. A detailed, physically based, one dimensional column snowpack model (Crocus) has been incorporated into the hydrological model, Weather Research and Forecasting (WRF)-Hydro, to allow for direct surface mass balance simulation of glaciers and subsequent modeling of meltwater discharge from glaciers. The new system (WRF-Hydro/Glacier) is only activated over a priori designated glacier areas. This glacier area is initialized with observed glacier thickness and assumed to be pure ice (with corresponding ice density). This allows for melting of the glacier to continue after all accumulated snow has melted. Furthermore, the simulation of surface albedo over the glacier is more realistic, as surface albedo is represented by snow, where there is accumulated snow, and glacier ice, when all accumulated snow is melted. To evaluate the WRF-Hydro/Glacier system over a glacier in southern Norway, WRF atmospheric model simulations were downscaled to 1 km grid spacing. This provided meteorological forcing data to the WRF-Hydro/Glacier system at 100 m grid spacing for surface and streamflow simulation. Evaluation of the WRF downscaling showed a good comparison with in situ meteorological observations for most of the simulation period. The WRF-Hydro/Glacier system reproduced the glacier surface winter/summer and net mass balance, snow depth, surface albedo and glacier runoff well compared to observations. The improved estimation of albedo has an appreciable impact on the discharge from the glacier during frequent precipitation periods. We have shown that the integrated snowpack system allows for improved glacier surface mass balance studies and hydrological studies.
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Givati, Amir, Barry Lynn, Yubao Liu, and Alon Rimmer. "Using the WRF Model in an Operational Streamflow Forecast System for the Jordan River." Journal of Applied Meteorology and Climatology 51, no. 2 (February 2011): 285–99. http://dx.doi.org/10.1175/jamc-d-11-082.1.
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AbstractThe Weather Research and Forecasting (WRF) model was employed to provide precipitation forecasts during the 2008/09 and 2009/10 winters (wet season) for Israel and the surrounding region where complex terrain dominates. The WRF precipitation prediction has been coupled with the Hydrological Model for Karst Environment (HYMKE) to forecast the upper Jordan River streamflow. The daily WRF precipitation forecasts were verified against the measurements from a dense network of rain gauges in northern and central Israel, and the simulation results using the high-resolution WRF indicated good agreement with the actual measurements. The daily precipitation amount calculated by WRF at rain gauges located in the upper parts of the Jordan River basin showed good agreement with the actual measurements. Numerical experiments were carried out to test the impact of the WRF model resolution and WRF microphysical schemes, to determine an optimal model configuration for this application. Because of orographic forcing in the region, it is necessary to run WRF with a 4–1.3-km grid increment and with sophisticated microphysical schemes that consider liquid water, ice, snow, and graupel to produce quality precipitation predictions. The hydrological modeling system that ingests the high-resolution WRF forecast precipitation produced good results and improved upon the operational streamflow forecast method for the Jordan River that is now in use. The modeling tools presented in this study are used to support the water-resource-assessment process and studies of seasonal hydroclimatic forecasting in this region.
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Liu, Zheng, Axel Schweiger, and Ron Lindsay. "Observations and Modeling of Atmospheric Profiles in the Arctic Seasonal Ice Zone." Monthly Weather Review 143, no. 1 (January 1, 2015): 39–53. http://dx.doi.org/10.1175/mwr-d-14-00118.1.
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Abstract The authors use the Polar Weather Research and Forecasting (WRF) Model to simulate atmospheric conditions during the Seasonal Ice Zone Reconnaissance Survey (SIZRS) in the summer of 2013 over the Beaufort Sea. With the SIZRS dropsonde data, the performance of WRF simulations and two forcing datasets is evaluated: the Interim ECMWF Re-Analysis (ERA-Interim) and the Global Forecast System (GFS) analysis. General features of observed mean profiles, such as low-level temperature inversion, low-level jet (LLJ), and specific humidity inversion are reproduced by all three models. A near-surface warm bias and a low-level moist bias are found in ERA-Interim. WRF significantly improves the mean LLJ, with a lower and stronger jet and a larger turning angle than the forcing. The improvement in the mean LLJ is likely related to the lower values of the boundary layer diffusion in WRF than in ERA-Interim and GFS, which also explains the lower near-surface temperature in WRF than the forcing. The relative humidity profiles have large differences between the observations, the ERA-Interim, and the GFS. The WRF simulated relative humidity closely resembles the forcings, suggesting the need to obtain more and better-calibrated humidity data in this region. The authors find that the sea ice concentrations in the ECMWF model are sometimes significantly underestimated due to an inappropriate thresholding mechanism. This thresholding affects both ERA-Interim and the ECMWF operational model. The scale of impact of this issue on the atmospheric boundary layer in the marginal ice zone is still unknown.
Dissertations / Theses on the topic "WRF Modeling"
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Melo, Camylla Maria Narciso de. "Using the WRF numerical model for the purpose of generation eolioelÃtrica: case study for MaracanaÃ, CearÃ." Universidade Federal do CearÃ, 2013. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=14606.
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FundaÃÃo Cearense de Apoio ao Desenvolvimento Cientifico e TecnolÃgicoThis paper analyzes the mesoscale model WRF (Weather Research And Forecast) to verify its reliability in use as a research tool in areas with potential for eolioeletric generation. The area chosen for study was a farm located in Maracanaà in the state of CearÃ. On the farm was installed an anemometer tower of 80 meters high with three anemometers, 1 windsock, 1 temperature sensor and a pyranometer, all sensors connected to a datalogger. The data collected in this tower were used for comparison with the data obtained through simulations in WRF. In the simulations the model was evaluated for two different climatic conditions in the region, the rainy and the dry seasons. The periods chosen to perform the simulations are: March/2012 (representing the rainy season) and November/2011 (representing the dry season). Was performed five sensitivity tests, which were exchanged in the parameterizations of the Planetary Boundary Layer (PBL), Surface Layer (CS) and Ground Surface Model (GSM). The simulation results were evaluated according to the Pearson's correlation method, that one has parameter values from -1 to 1 which presents an index of correlations ranging from bad (-1) to great (1). The simulation with the best performance in the dry and rainy periods presented values for correlations of 0.76 and 0.58, respectively, considered good and fair to the Pearson's parameters. The model was able to satisfactorily represent the local wind behavior for the dry season of the year, and more research is needed in the area to analyze how the model behaves in the representation of the rainy season. Thus, this model provides satisfactory results to be used as a tool for evaluate areas with potential for eolioeletric generation, more research is needed to fit better.
O presente trabalho analisa o modelo de mesoescala WRF (Weather Research and Forecast) para verificar a sua confiabilidade na utilizaÃÃo como ferramenta de investigaÃÃo de Ãreas com potencial para geraÃÃo eolioelÃtrica. A regiÃo escolhida para estudo foi uma fazenda localizada no municÃpio de MaracanaÃ, no estado do CearÃ. Na fazenda foi instalada uma torre anemomÃtrica de 80 metros de altura com 3 anemÃmetros, 1 biruta, 1 sensor de temperatura e um piranÃmetro, todos os sensores conectados a um datalogger. Os dados coletados nesta torre foram utilizados para comparaÃÃo com os dados obtidos atravÃs das simulaÃÃes no WRF. Nas simulaÃÃes o modelo foi avaliado para duas situaÃÃes climatolÃgicas distintas na regiÃo, o perÃodo chuvoso e o seco. Os perÃodos escolhidos para realizar as simulaÃÃes sÃo: marÃo/2012 (representando o perÃodo chuvoso) e novembro/2011 (representando o perÃodo seco). Foram realizados cinco testes de sensibilidade, nos quais foram permutadas as parametrizaÃÃes da Camada Limite PlanetÃria (CLP), Camada de SuperfÃcie (CS) e o Modelo de Solo SuperfÃcie (MSS). Os resultados das simulaÃÃes foram avaliados segundo o mÃtodo de correlaÃÃo de Pearson, mÃtodo este que possui parÃmetros de valores de -1 a 1 onde apresenta um indicativo de correlaÃÃes que vÃo de pÃssimas (-1) a Ãtimas (1). A simulaÃÃo com o melhor desempenho no perÃodo seco e chuvoso apresentaram valores de correlaÃÃes de 0,76 e 0,58, consideradas forte e moderada, para os parÃmetros de Pearson, respectivamente. O modelo conseguiu representar de forma satisfatÃria o regime de vento local para a estaÃÃo seca do ano, sendo necessÃrias mais pesquisas na Ãrea para analisar como o modelo se comporta na representaÃÃo do perÃodo chuvoso. Assim este modelo apresenta resultados satisfatÃrios para ser utilizado como ferramenta para avaliaÃÃo de regiÃes com potencial em geraÃÃo eolioelÃtrica, sendo necessÃrias mais pesquisas para ajustÃ-lo melhor.
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Yu, Man. "An assessment of urbanization impact in China by using WRF-Chem and configuration optimization." Diss., University of Iowa, 2014. https://ir.uiowa.edu/etd/1814.
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Urbanization is an inevitable process for every developing and developed country. In China this process accelerated after the reform and open-door policies initialed in 1980s. Urbanization can bring tremendous influences on air quality and in turn adverse health effects. Therefore it is of importance to access and evaluate urbanization process. In this Thesis, we focus on three major impacts in China: land-cover change (from nature land type to urban land type), anthropogenic heat emission (due to human activity), and pollutant emission increase (mainly from industry, power, transportation and residential). The model tool used in this paper is called WRF-Chem (the fully coupled Weather Research and Forecast Model with Chemistry Module). After designing and performing three different sensitivity runs, it turns out that all of these three impacts from urbanization tend to worsen air quality conditions in Beijing, especially for ozone and PM2.5 concentrations. The first impact from land-cover change in Chapter 2 increases temperature by 2.4 C; for Beijing and ozone by 20 ppb. Adding human heat release (the second impact) also increases surface temperature by 0.8 C; at daytime and 1.2 C; at nighttime (Chapter 4). Consequently, model outputs a more polluted scenario in Beijing, with 18 ppb more ozone during nocturnal time. When exploring the third impact from emission change, we found out that the government's mitigation regulations on emissions in Beijing has in effect. Around Beijing area, the emissions for CO and SO2 remains the same level from 2006 to 2010, while other cities inside North China Plain are experiencing rapid growths in anthropogenic emissions. Results show a slightly increase in surface temperature and ozone concentrations. Meanwhile, the concentration of particulate matters tends to increase near surface and decrease in the upper atmosphere. For future study, it is highly recommended to include these impacts into model configurations. Additional sensitivity runs were conducted to optimize forecast computing in China, concerning both spatial and vertical resolutions. This sensitivity studies represented 4 different grid resolutions and three different vertical meshes. Regards to the analysis with available observation data, a resolution of 9 km and 27 vertical layers is determined to be the best option for future efficient and accurate forecasts in China. For horizontal aspects, both 81-km and 27-km resolutions are not able to capture pollutant distributions and no significant discrepancy is found out between 9-km and 3-km case. In vertical resolution sensitivity runs, we use 9 layers, 27 layers, and 54 layers mesh with same top and bottom staggers. Analysis reveals totally different vertical profile between 9 layers and 27 layers cases and similar profile between 27 layers and 54 layers. Therefore, we recommend spatial settings with 9-km resolution and a vertical mesh with 27 layers. Finally, the updated 3-d model, involving three urbanization impacts and using recommended resolution settings is used to support a field campaign in summer 2013 for North China Plain. Some preliminary results show a confidence using our model, by capturing both meteorological and chemical trends in Beijing.
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Iotti, Marcello. "Urban boundary layer modeling with WRF: assessment of different urban parameterizations over the city of Bologna." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
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Urbanization affects all the components of the Earth system, clearly including the atmosphere. It is therefore important the understanding of cities-related processes and their representation in modeling terms. Many different spatial scales pertain urban modeling: processes linked to a single building or to an
urban district are well represented with microscale methods, but the city as a whole has influences traceable at the mesoscale, a domain traditionally linked to numerical weather prediction (NWP) models. It is evident the discontinuity of these approaches and the advantage that one would have in connecting them, so that buildings-atmosphere interactions are properly considered in mesoscale atmospheric simulations.
Within the Weather Research and Forecasting Model (WRF) community various urban parameterizations, with different degree of sophistication, have been developed. In recent years they have found notable applications, but literature focuses mainly on large cities. The purpose of this work is a comparative evaluation of these parameterizations, applied to a medium-sized city such as Bologna.
Their accuracy was evaluated using temperature, wind speed and wind direction data recorded by a set of measurement stations. Finally the spatial structure of 2 m-air temperature and 10 m-wind fields was examined, highlighting the different behavior of urban parameterizations on the city area of Bologna.
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Tastula, Esa-Matti. "Insights into the Challenges of Modeling the Atmospheric Boundary Layer." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5782.
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This work approaches the topic of modeling the atmospheric boundary layer in four research projects, which are summarized below.
i) The diurnal cycles of near-surface meteorological parameters over Antarctic sea ice in six widely used atmospheric reanalyses were validated against observations from Ice Station Weddell. The station drifted from February through May 1992 and provided the most extensive set of meteorological observations ever collected in the Antarctic sea ice zone. For the radiative and turbulent surface fluxes, both the amplitude and shape of the diurnal cycles varied considerably among different reanalyses. Near-surface temperature, specific humidity, and wind speed in the reanalyses all featured small diurnal ranges, which, in most cases, fell within the uncertainties of the observed cycle. A skill score approach revealed the superiority of the ERA-Interim reanalysis in reproducing the observed diurnal cycles. An explanation for the shortcomings in the reanalyses is their failure to capture the diurnal cycle in cloud cover fraction, which leads to errors in other quantities as well. Apart from the diurnal cycles, NCEP-CFSR gave the best error statistics.
ii) The accuracy of prediction of stable atmospheric boundary layers depends on the parameterization of the surface layer which is usually derived from the Monin-Obukhov similarity theory. In this study, several surface-layer models in the format of velocity and potential temperature Deacon numbers were compared to observations from CASES-99, Cardington, and Halley datasets. The comparisons were hindered by a large amount of scatter within and among datasets. Tests utilizing R2 demonstrated that the Quasi-Normal Scale Elimination (QNSE) theory exhibits the best overall performance. Further proof of this was provided by 1D simulations with the Weather Research and Forecasting (WRF) model.
iii) The increasing number of physics parameterization schemes adopted in numerical weather forecasting models has resulted in a proliferation of inter-comparison studies in recent years. Many of these studies concentrated on determining which parameterization yields results closest to observations rather than analyzing the reasons underlying the differences. In this work, the performance of two 1.5-order boundary layer parameterizations was studied, the QNSE and Mellor-Yamada-Janjić (MYJ) schemes, in the Weather Research and Forecasting (WRF) model. The objectives were to isolate the effect of stability functions on the near-surface values and vertical profiles of virtual temperature, mixing ratio and wind speed. The results demonstrate that the QNSE stability functions yield better error statistics for 2-m virtual temperature but higher up the errors related to QNSE are slightly larger for virtual temperature and mixing ratio. A surprising finding is the sensitivity of the model results to the choice of the turbulent Prandtl number for neutral stratification (Prt0): in the Monin-Obukhov similarity function for heat, the choice of Prt0 is sometimes more important than the functional form of the similarity function itself. There is a stability-related dependence to this sensitivity: with increasing near-surface stability, the relative importance of the functional form increases. In near-neutral conditions, QNSE exhibits too strong vertical mixing attributed to the applied turbulent kinetic energy subroutine and the stability functions including the effect of Prt0.
iv) In recent years, many eddy-diffusivity mass flux (EDMF) planetary boundary layer (PBL) parameterizations have been introduced. Yet, most validations are based on idealized setups and/or single column models. To address this gap, this study focused on the effect the mass flux part has on the performance in the QNSE-EDMF PBL scheme in the WRF model by comparing the results to observations from the CASES-97 field campaign. In addition, two refined versions, one introducing the parameterized clouds to the WRF radiation scheme, and the second adding a different entrainment formulation, were evaluated. The introduction of mass flux reduced errors in the average moisture profile but virtual temperature and wind speed profiles did not change as much. The turbulent flux profiles for modeled virtual potential temperature were little affected, with consistent reasonable agreement with observations, if one allows for biases in the observed data and modeled surface fluxes. However, the water vapor flux divergences from QNSE tend to be more negative than observed, while including the mass flux part tends to make the divergences more positive, the latter at least partially due to deeper model PBLs resulting from excessive model surface virtual temperature fluxes. Further, both virtual potential temperature and water vapor flux profiles display spurious spikes attributed to the way the non-local and local terms interact in the model. The influence of the mass flux schemes extends to 60 – 100-km scale circulation features, which were greatly modified by both the inclusion of mass flux and the new entrainment formulation. Adding mass flux based clouds to the radiation calculation improved the time and space averaged modeled incoming shortwave flux. The choice of the representation for entrainment/detrainment often affected the results to the same extent as adding mass flux did.
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Wille, Jonathan D. "Analysis of the AMPS-Polar WRF Boundary Layer at the Alexander Tall Tower! site on the Ross Ice Shelf." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1437500291.
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MARTINS, Rafael Castelo Guedes. "Estudo da sensibilidade do modelo WRF às parametrizações de microfísica de nuvens e à assimilação de dados observados." Universidade Federal de Campina Grande, 2014. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1466.
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RAFAEL CASTELO GUEDES MARTINS – TESE (PPGMet) 2014.pdf: 3362803 bytes, checksum: 5a99c28e73f6a95fef76f82f96d2edc4 (MD5)Made available in DSpace on 2018-08-15T19:02:39Z (GMT). No. of bitstreams: 1 RAFAEL CASTELO GUEDES MARTINS – TESE (PPGMet) 2014.pdf: 3362803 bytes, checksum: 5a99c28e73f6a95fef76f82f96d2edc4 (MD5) Previous issue date: 2014-12-12
Um dos principais desafios atuais da modelagem numérica da atmosfera trata da previsão quantitativa da precipitação e do posicionamento das nuvens de chuva. Este trabalho tem com o principal objetivo avaliar o desempenho das arametrizações de microfísicas na modelagem regional com ênfase no papel da informação de grande escala e sua influência sobre as simulações, e no uso de dados observados de radiossondagens como forma de acrescentar informação à modelagem . Inicialmente, duas reanálises (NCEP2 e ERAI) foram estatisticamente comparadas com dados de PCDs do Estado do Ceará. Verificou - se qu e a ERAI apresentou maior semelhança com as observações, principalmente para as variáveis diretamente ligadas à convecção. Em seguida, a ERAI foi utilizada como forçamento de grande escala em simulações com o modelo WRF. Observou- se que o uso de microfísica detalhada não melhora necessariamente a previsão do modelo, caso não sejam utilizados dados observados no local de estudo. Por último, duas simulações de alta resolução foram realizadas. Uma forçada pela reanálise sem modificação e outra forçada pela reanálise modificada utilizando o método de análise objetiva do WRF, para incluir as séries temporais de radiossondagens coletadas durante campanha experimental do Projeto CHUVA, em Fortaleza- CE. As duas simulações foram comparadas com dados observados pelo radiômetro para o mesmo local e período das radiossondagens . Observou - se que a inclusão das observações de sondagens na modelagem possibilita melhor modelagem de um sistema convectivo ocorrido em abril de 2011, principalmente para as variáveis ligadas à convecção. Este trabalho aponta, utilizando análises comparativas e estatísticas, que a utilização de uma maior densidade de dados observacionais válidos no modelo pode melhorar de forma muito mais eficiente o resultado da modelagem, do que mesmo a utilização do downscaling dinâmico do dado de grande escala ou a utilização de esquemas de microfísica detalhada, que, em algumas situações, pode inclusive inserir mais erros nos sistema s modelados.
The quantitative prediction of precipitation and the positioning of the rain clouds is one of the main challenges of numerical modeling of the atmosphere in present days. This work aims to evaluate the performance of the microphysical parameterizations in regional modeling, with emphasis on the role of large- scale information and its influence on the simulations, and the use of observational data from radiosondes as a way to add information to modeling. Initially, two reanalysis (NCEP2 and ERAI) were statistically compared with data from PCDs from the Ceará State. It was found that the ERAI showed similarity to the observations, especially for variables directly linked to convection. Then, the ERAI is used as large scale forcing in simulations with the WRF model. It was observed that the use of detailed microphysics does not necessarily improve the model performance, if in situ data were not used. Finally, two high resolution simulations were performed. The first f orced by reanalysis without modification and other forced by reanalysis using the modified method of objective analysis of the WRF, to include the time series of radiosonde observations collected during the experimental campaign of the CHUVA Project in Fortaleza- CE. The two simulations were compared with data observed by the radiometer to the same place and period of the radiosonde. It was observed that the inclusion of radiosonde observations in to the model leads to a better simulation of a convective system that occurred in April 2011, mostly for the variables related to convection. Using comparative statistical analysis, t his work points that the use of a higher density of valid observational data in the model can improve much more efficiently the model results than the use of a dynamic downscal ing of large- scale data or the use of schemes with detailed microphysics, which in some circumstances may even introduce more errors into the modeled system s.
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Lawless, Zachary David. "Modeling Current and Future Windblown Utah Dust Events Using CMAQ 5.3.1." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9165.
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Windblown dust events can be defined as windblown dust emitted from the Earth's surface to the atmosphere. These events have significant impact on local air quality. Predicting the location and magnitude of these events is vital for Utah air quality assessment and planning. Previous modeling studies have focused only on past dust events. This work utilized a state-of-the-science software framework based on the Community Multiscale Air Quality (CMAQ) v5.3.1 modeling system to predict dust events in Utah. The framework was verified using previous studies for dust events in April 2017 and March 2010. Once verified, the framework was used to predict the impact of future land use properties on dust events. Two scenarios were studied – shrinking of the Great Salt Lake and the addition of large-scale solar farms west of the Wasatch Front. Both showed increases in dust concentrations overpopulated areas using the meteorological conditions from the April 2017 dust event. Such information from future impact studies can assess potential impacts from climate change and can guide government water and land use policies to mitigate dust event impacts.
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Santoni, Gregory Winn. "Fluxes of Atmospheric Methane Using Novel Instruments, Field Measurements, and Inverse Modeling." Thesis, Harvard University, 2013. http://dissertations.umi.com/gsas.harvard:10941.
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The atmospheric concentration of methane \((CH_4)\) - the most significant non-\(CO_2\) anthropogenic long-lived greenhouse gas - stabilized between 1999 and 2006 and then began to rise again. Explanations for this behavior differ but studies agree that more measurements and better modeling are needed to reliably explain the model-data discrepancies and predict future change. This dissertation focuses on measurements of \(CH_4\) and inverse modeling of atmospheric \(CH_4\) fluxes using field measurements at a variety of spatial scales. We first present a new fast-response instrument to measure the isotopic composition of \(CH_4\) in ambient air. The instrument was used to characterize mass fluxes and isofluxes (a isotopically-weighted mass flux) from a well-studied research fen in New Hampshire. Eddy-covariance and automatic chamber techniques produced consistent estimates of both the \(CH_4\) fluxes and their isotopic composition at sub-hourly resolution. We then characterize fluxes of \(CH_4\) from aircraft engines using measurements made with the same instrument during the Alternative Aviation Fuel Experiment (AAFEX), a study that aimed to determine the atmospheric impacts of alternative fuel use in the growing aviation industry. Emissions of \(CO_2\), \(CH_4\), and \(N_2O\) from different synthetic fuels were statistically indistinguishable from those of the widely used JP-8 jet fuel. We then present airborne observations of the long-lived greenhouse gas suite – \(CO_2\), \(CH_4\), \(N_2O\), and CO – during two aircraft campaigns, HIPPO and CalNex, made using a similar instrument built specifically for the NCAR HIAPER GV aircraft. These measurements are compared to data from other onboard sensors and show excellent agreement. We discuss the details of the end-to-end calibration procedures and the data quality-assurance and quality-control (QA/QC). Lastly, we quantify a top-down estimate of California’s \(CH_4\) emission inventory using the CalNex \(CH_4\) observations. Observed \(CH_4\) enhancements above background concentrations are simulated using a lagrangian transport model driven by validated meteorology. A priori source-specific emission inventories are optimized in a Bayesian inversion framework to show that California’s \(CH_4\) budget is 1.6 ± 0.34 times larger than the current estimate of California’s Air Resources Board (CARB), the body charged with enforcing the California Global Solutions Act and tracking emission changes over time. Findings highlight large underestimates of emissions from cattle and natural gas infrastructure.Earth and Planetary Sciences
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Darmenov, Anton. "Developing and testing a coupled regional modeling system for establishing an integrated modeling and observational framework for dust aerosol." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28217.
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Thesis (M. S.)--Earth and Atmospheric Sciences, Georgia Institute of Technology, 2009.Committee Chair: Sokolik, Irina; Committee Member: Curry, Judith; Committee Member: Kalashnikova, Olga; Committee Member: Nenes, Athanasios; Committee Member: Stieglitz, Marc.
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Silva, Natália Pillar da. "Estudo dos Mecanismos Vinculados ao Estabelecimento de um Evento de ZCAS Através de Simulações com o Modelo WRF." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/14/14133/tde-03082018-101530/.
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No presente estudo, os mecanismos vinculados à formação de um intenso evento de Zona de Convergência do Atlântico Sul (ZCAS) foram investigados. Para isso, uma análise observacional foi realizada para identificação desse sistema e seguinte implementação de um estudo numérico em uma escala sub-sazonal. Uma vez que a atividade da ZCAS é predominantemente concentrada em uma das regiões de maior importância socioeconômica da América do Sul, os estudos de previsibilidade dessa feição são extremamente importantes. O evento escolhido pela análise observacional foi caracterizado pelo suporte de uma estrutura em larga escala para seu desenvolvimento e persistência, através da presença de um vórtice ciclônico na região costeira do sudeste do Brasil. A representação numérica desse caso de ZCAS foi particularmente desafiadora, uma vez que trata-se de um sistema complexo, cujo desenvolvimento e evolução conectam-se a características atmosféricas de grande escala. Para aprimorar a representação numérica desse evento, várias aplicações utilizando-se nudging espectral foram testadas, para garantir que as características de grande escala que suportam o sistema fossem bem representadas pelo modelo numérico. Os resultados mostram que a alternativa menos restritiva para a aplicação do nudging espectral mostrou-se ideal para manter suas características importantes, e ainda permitindo que os componentes físicos do modelo contribuam com a representação da atmosfera em escalas menores. A partir disso, novos experimentos numéricos foram conduzidos para uma avaliação de como diferentes parametrizações convectivas e microfísica representam a banda de precipitação associada ao sistema. Os resultados mostram que, quando usados juntos, tanto a opção de microfísica WRF Single Moment 6-Class (WSM6) quanto a opção cumulus de Kain-Fritsch (KF) contribuíram para a formação da banda convectiva associada à ZCAS. Os resultados também mostram que é possível usar um esquema de microfísica mais simples (WSM3) para a representação do sistema, uma vez que os desempenhos entre os diferentes testes em microfísica foram semelhantes.In the present study, the mechanisms and formation of an intense South Atlantic Convergence Zone (SACZ) event were investigated. For this, an observational analysis was performed to identify this system for the implementation of a numerical study on a sub-seasonal scale. Since the SACZ activity is predominantly concentrated over one of the most socioeconomically important regions of South America, predictability studies for this system are extremely valuable. The SACZ event chosen by the observational analysis was supported by a large-scale structure that featured a cyclonic vortex in the coastal region of southeastern Brazil. The numerical representation of a SACZ case in this context was particularly challenging since the SACZ is a very complex system and its development and evolution are closely linked to large-scale atmospheric features. To improve the numerical representation of such event, several spectral nudging applications were tested to ensure the large scale features that support the systems are well represented by the numerical model. Results show that the less restrictive alternative for the spectral nudging application was ideal for maintaining important features in large scales while still allowing the physical components of the model to contribute the representation of the atmosphere on smaller scales. From this, numerical experiments were conducted for an evaluation of how different convective parametrizations and microphysics represent the precipitation band associated to the system. The results show that, when used together, both WRF Single Moment 6-Class (WSM6) microphysics option and Kain-Fritsch (KF) cumulus option contributed to the formation of convective band associated with the SACZ. Results also show that it is possible to use a simpler microphysics scheme (WSM3) for the representation of the system, since the performances between different tests in microphysics were similar.
Books on the topic "WRF Modeling"
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Methods for Wastewater Characterization in Activated Sludge Modelling: Werf Report Project 99-wwf-3 (Werf Report). Water Environment Research Foundation, 2005.
Find full textBook chapters on the topic "WRF Modeling"
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Werner, Małgorzata, Maciej Kryza, Kinga Wałaszek, Massimo Vieno, and Anthony J. Dore. "EMEP4PL and WRF-Chem—Evaluation of the Modelling Results." In Air Pollution Modeling and its Application XXV, 117–22. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57645-9_18.
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Balzarini, A., L. Honzak, G. Pirovano, G. M. Riva, and R. Zabkar. "WRF-Chem Model Sensitivity Analysis to Chemical Mechanism Choice." In Air Pollution Modeling and its Application XXIII, 557–61. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_92.
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Kumar, S., A. Routray, G. Tiwari, R. Chauhan, and I. Jain. "Simulation of Tropical Cyclone ‘Phailin’ Using WRF Modeling System." In Tropical Cyclone Activity over the North Indian Ocean, 307–16. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40576-6_21.
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Tuccella, Paolo, Gabriele Curci, Suzanne Crumeyrolle, and Guido Visconti. "Modeling of Aerosol Indirect Effects with WRF/Chem over Europe." In Air Pollution Modeling and its Application XXIII, 91–95. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_15.
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Balzarini, A., F. Angelini, L. Ferrero, M. Moscatelli, G. Pirovano, G. M. Riva, A. Toppetti, and E. Bolzacchini. "Comparing WRF PBL Schemes with Experimental Data over Northern Italy." In Air Pollution Modeling and its Application XXIII, 545–49. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_90.
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Zhang, Yang, Xin Zhang, Changjie Cai, Kai Wang, and Litao Wang. "Studying Aerosol-Cloud-Climate Interactions over East Asia Using WRF/Chem." In Air Pollution Modeling and its Application XXIII, 61–66. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_10.
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Hogrefe, Christian, Stefano Galmarini, Shawn Roselle, and Rohit Mathur. "AQMEII Phase 2: Overview and WRF-CMAQ Application Over North America." In Air Pollution Modeling and its Application XXIII, 463–66. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_76.
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Gašparac, Goran, Amela Jeričević, and Branko Grisogono. "Influence of WRF Parameterization on Coupled Air Quality Modeling Systems." In Springer Proceedings in Complexity, 557–61. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-24478-5_90.
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Fallmann, Joachim, Stefan Emeis, and Peter Suppan. "Modeling of the Urban Heat Island and its effect on Air Quality using WRF/WRF-Chem – Assessment of mitigation strategies for a Central European city." In Air Pollution Modeling and its Application XXIII, 373–77. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_60.
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Knote, Christoph, Alma Hodzic, Jose L. Jimenez, Rainer Volkamer, John J. Orlando, Sunil Baidar, Jerome Brioude, et al. "Novel Pathways to Form Secondary Organic Aerosols: Glyoxal SOA in WRF/Chem." In Air Pollution Modeling and its Application XXIII, 149–54. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-04379-1_24.
Full textConference papers on the topic "WRF Modeling"
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Elmer, Nicholas, Christopher Hain, James McCreight, and David Gochis. "SWOT Applications for WRF-Hydro Modeling in Alaska." In IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2020. http://dx.doi.org/10.1109/igarss39084.2020.9323136.
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Li, X., W. Zheng, and D. Shen. "SAR Observations and WRF Modeling of Marine Atmospheric Phenomena." In 2018 Progress in Electromagnetics Research Symposium (PIERS-Toyama). IEEE, 2018. http://dx.doi.org/10.23919/piers.2018.8597982.
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He, Wenying. "Comparisons of radiative transfer models for GMI assimilation in WRF." In Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions VII, edited by Guosheng Liu and Ziad S. Haddad. SPIE, 2018. http://dx.doi.org/10.1117/12.2324674.
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Polezhayeva, Antonina, and Antonina Polezhayeva. "NUMERICAL MODELING OF POLAR LOWS OVER THE BARENTS SEA: IMPACT OF WRF PARAMETRIZATIONS ON THE QUALITY OF FORECAST." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.21610/conferencearticle_58b43155456a5.
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Polar lows are generally characterized by severe weather in the form of strong winds, showers and occasionally heavy snow, which have sometimes resulted in the loss of life, especially at sea. Numerical simulations with mesoscale atmospheric models is a good alternative to investigate polar low phenomenon, because they produce temporally and spatially regular-spaced fields of atmospheric variables with high resolution. To describe the evolution of atmospheric processes the Advanced Weather Research and Forecasting (WRF-ARW) model was used. The principal objectives of this study were 1) the understanding of mesoscale WRF model and adapting the model for the Barents Sea region; 2) to conduct numerical experiments using WRF model with different Planetary Boundary Layer parameterization (PBLs) schemes and investigate the impact of each scheme on the quality of forecast; and 3) the investigation of the capability of WRF model to successfully simulate evolution of polar lows. The impact on the quality of forecast was investigated. The results of the study, obtained by numerical modeling of polar mesoscale low over the Barents Sea. One polar low, near Spitsbergen, from 24 of March to 26 of March 2014 were targeted. The results of numerical experiments showed that each of Planetary Boundary Layer parameterization scheme isn't successful for simulation of polar low.
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Polezhayeva, Antonina, and Antonina Polezhayeva. "NUMERICAL MODELING OF POLAR LOWS OVER THE BARENTS SEA: IMPACT OF WRF PARAMETRIZATIONS ON THE QUALITY OF FORECAST." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.31519/conferencearticle_5b1b9387834ac4.45240165.
Full textAbstract:
Polar lows are generally characterized by severe weather in the form of strong winds, showers and occasionally heavy snow, which have sometimes resulted in the loss of life, especially at sea. Numerical simulations with mesoscale atmospheric models is a good alternative to investigate polar low phenomenon, because they produce temporally and spatially regular-spaced fields of atmospheric variables with high resolution. To describe the evolution of atmospheric processes the Advanced Weather Research and Forecasting (WRF-ARW) model was used. The principal objectives of this study were 1) the understanding of mesoscale WRF model and adapting the model for the Barents Sea region; 2) to conduct numerical experiments using WRF model with different Planetary Boundary Layer parameterization (PBLs) schemes and investigate the impact of each scheme on the quality of forecast; and 3) the investigation of the capability of WRF model to successfully simulate evolution of polar lows. The impact on the quality of forecast was investigated. The results of the study, obtained by numerical modeling of polar mesoscale low over the Barents Sea. One polar low, near Spitsbergen, from 24 of March to 26 of March 2014 were targeted. The results of numerical experiments showed that each of Planetary Boundary Layer parameterization scheme isn't successful for simulation of polar low.
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Luna, Marco Guevara, Luis Carlos Belalcazar Ceron, and Alain Clappier. "Implementation and validation of the performance of meteorological modeling with WRF in Colombian cities." In 2019 Congreso Colombiano y Conferencia Internacional de Calidad de Aire y Salud Pública (CASP). IEEE, 2019. http://dx.doi.org/10.1109/casap48673.2019.9364068.
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Mall, Martin, Ulo Suursaar, Tomoya Shibayama, and Ryota Nakamura. "Modeling Cyclone-Related Precipitation Changes in Future Climates Using WRF Model and CMIP5 Output Data." In IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2019. http://dx.doi.org/10.1109/igarss.2019.8900309.
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González, Jorge E., and Estatio Gutierrez. "On the Environmental Sensible/Latent Heat Fluxes From A/C Systems in Urban Dense Environments: A New Modeling Approach and Case Study." In ASME 2015 9th International Conference on Energy Sustainability collocated with the ASME 2015 Power Conference, the ASME 2015 13th International Conference on Fuel Cell Science, Engineering and Technology, and the ASME 2015 Nuclear Forum. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/es2015-49583.
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Recent trends for denser cities and associated levels of human activity reflected in energy demands are requiring new ways for quantifying human environmental impacts in cities. There is little information on human-induced environmental heat fluxes from very dense urban environments, and far less information on the anthropogenic sensible/latent heat flux partition. To address this, a surface energy model that takes into account evaporation from impervious surfaces and from cooling towers from buildings was implemented in the multilayer urban canopy model (BEP+BEM) of the Weather Forecasting Research (WRF) model to estimate the overall sensible/latent heat fluxes from urban surfaces and from air condition (A/C) systems from buildings in complex urban environments. The scenario used as case study was New York City (NYC) during summers (2010 & 2013). Urban canopy parameters from the Department of City Planning of NYC were assimilated into WRF with BEP+BEM at 250 meters horizontal resolution to have an accurate representation of the city topology. The modeling approach was calibrated with surface weather stations in NYC showing general good agreement with slight tendency to overestimate maximum temperatures and underestimate moisture content at nighttime. The A/C component was estimated in 150W/m2 latent heat due to cooling towers, and close to 40 W/m2 in sensible. Evaporative cooling technology diminishes between 80 and 90% the amount of sensible heat which is transformed into latent heat. Impacts of anthropogenic in the Planetary Boundary Layer (PBL) reflect warm season increases in the PBL height, and significant increases of atmospheric instability.
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Fomin, Vladimir, Vladimir Fomin, Dmitrii Alekseev, Dmitrii Alekseev, Dmitrii Lazorenko, and Dmitrii Lazorenko. "NUMERICAL MODELING OF STORM SURGES, WIND WAVES AND FLOODING IN THE TAGANROG BAY." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.21610/conferencearticle_58b43153f04bb.
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Storm surges and wind waves are ones of the most important hydrological characteristics, which determine dynamics of the Sea of Azov. Extreme storm surges in Taganrog Bay and flooding in the Don Delta can be formed under the effect of strong western winds. In this work the sea level oscillations and wind waves in the Taganrog Bay were simulated by means of the coupled SWAN+ADCIRC numerical model, taking into account the flooding and drying mechanisms. The calculations were carried out on an unstructured mesh with high resolution. The wind and atmospheric pressure fields for the extreme storm from 20 to 28 of September, 2014 obtained from WRF regional atmospheric model were used as forcing. The analysis of simulation results showed the following. The western and northern parts of the Don Delta were the most flood-prone during the storm. The size of the flooded area of the Don Delta exceeded 50%. Interaction of storm surge and wind wave accelerated the flooding process, increased the size of the flooded area and led to the intensification of wind waves in the upper of Taganrog Bay due to the general rise of the sea level.
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Fomin, Vladimir, Vladimir Fomin, Dmitrii Alekseev, Dmitrii Alekseev, Dmitrii Lazorenko, and Dmitrii Lazorenko. "NUMERICAL MODELING OF STORM SURGES, WIND WAVES AND FLOODING IN THE TAGANROG BAY." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.31519/conferencearticle_5b1b936e654216.92483473.
Full textAbstract:
Storm surges and wind waves are ones of the most important hydrological characteristics, which determine dynamics of the Sea of Azov. Extreme storm surges in Taganrog Bay and flooding in the Don Delta can be formed under the effect of strong western winds. In this work the sea level oscillations and wind waves in the Taganrog Bay were simulated by means of the coupled SWAN+ADCIRC numerical model, taking into account the flooding and drying mechanisms. The calculations were carried out on an unstructured mesh with high resolution. The wind and atmospheric pressure fields for the extreme storm from 20 to 28 of September, 2014 obtained from WRF regional atmospheric model were used as forcing. The analysis of simulation results showed the following. The western and northern parts of the Don Delta were the most flood-prone during the storm. The size of the flooded area of the Don Delta exceeded 50%. Interaction of storm surge and wind wave accelerated the flooding process, increased the size of the flooded area and led to the intensification of wind waves in the upper of Taganrog Bay due to the general rise of the sea level.
Reports on the topic "WRF Modeling"
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LeGrand, Sandra, Christopher Polashenski, Theodore Letcher, Glenn Creighton, Steven Peckham, and Jeffrey Cetola. The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41560.
Full textAbstract:
Airborne particles of mineral dust play a key role in Earth’s climate system and affect human activities around the globe. The numerical weather modeling community has undertaken considerable efforts to accurately forecast these dust emissions. Here, for the first time in the literature, we thoroughly describe and document the Air Force Weather Agency (AFWA) dust emission scheme for the Georgia Institute of Technology–Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosol model within the Weather Research and Forecasting model with chemistry (WRF-Chem) and compare it to the other dust emission schemes available in WRF-Chem. The AFWA dust emission scheme addresses some shortcomings experienced by the earlier GOCART-WRF scheme. Improved model physics are designed to better handle emission of fine dust particles by representing saltation bombardment. WRF-Chem model performance with the AFWA scheme is evaluated against observations of dust emission in southwest Asia and compared to emissions predicted by the other schemes built into the WRF-Chem GOCART model. Results highlight the relative strengths of the available schemes, indicate the reasons for disagreement, and demonstrate the need for improved soil source data.