Evaluating the performance of WRF urban schemes and PBL schemes over Dallas Fort Worth during a dry summer and a wet summer

2020 ◽  
Author(s):  
Jinxin Wang ◽  
Xiao-Ming Hu
Keyword(s):  
Wind Speed ◽  
Wrf Model ◽  
Canopy Temperature ◽  
Single Layer ◽  
Urban Canopy ◽  
Superior Performance ◽  
Fort Worth ◽  
Building Height ◽  
Road Width ◽  
Urban Cool Island

AbstractThis study evaluated the Weather Research and Forecasting (WRF) model sensitivity to different planetary boundary layer (PBL) schemes (the YSU and MYJ schemes) and urban schemes including the bulk scheme (BULK), single-layer urban canopy model (UCM), multi-layer building environment parameterization (BEP) model, and multi-layer building energy model (BEM). Daily reinitialization simulations were conducted over Dallas-Fort Worth during a dry summer month (July 2011) and a wet summer month (July 2015) with weaker (stronger) daytime (nocturnal) UHI in 2011 than 2015. All urban schemes overestimated the urban daytime 2m temperature in both summers, but BEP and BEM still reproduced the daytime urban cool island in dry summer. All urban schemes reproduced the nocturnal urban heat island, with BEP producing the weakest one due to its unrealistic urban cooling. BULK and UCM overestimated the urban canopy wind speed, while BEP and BEM underestimated it. The urban schemes showed prominent impact on daytime PBL profiles. UCM+MYJ showed a superior performance than other configurations. The relatively large (small) aspect ratio between building height and road width in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy temperature. The relatively low (high) building height in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy wind speed. Improving urban schemes and providing realistic urban parameters were critical for improving urban canopy simulation.

Simulation of Downstream Effects of Urbanization on Cloud and Precipitation with WRF Model in Yangtze River Delta, China

2020 ◽  
Author(s):  
Xiaomen Han ◽  
Jianning Sun
Keyword(s):  
Yangtze River ◽  
Vertical Mixing ◽  
Wrf Model ◽  
Single Layer ◽  
Urban Canopy ◽  
Yangtze River Delta ◽  
River Delta ◽  
Dominant Factor ◽  
Urbanization Effect ◽  
Downstream Effects

<p>Urbanization, one of the extreme cases of land-use change, plays an important role in modifying precipitation and urban hydrology. In this study, urbanization effect on cloud and precipitation in the Yangtze River Delta of China is simulated using Weather Research and Forecasting (WRF) model coupled with a single-layer Urban Canopy Model(SLUCM). Based on the 4-summer simulation results from 2011 to 2014, we find that the influence of cities on clouds and precipitation is obviously affected by wind field. During the day, more cloud on higher level and precipitation occurs in urban area and downwind region of urban, induced by more unstable urban air transported downstream, which enhances vertical mixing and updraft moisture transport. At night, the urban dry island become the dominant factor, resulting in the decrease of cloud occurrence in the urban and downstream areas. The downstream effects of urbanization on cloud and precipitation turn out to be strongly related to the moisture and convective conditions.</p><p> </p>

Sensitivity of Predictions of the Urban Surface Energy Balance and Heat Island to Variations of Urban Canopy Parameters in Simulations with the WRF Model

2017 ◽  
Vol 56 (3) ◽  
pp. 573-595 ◽  
Author(s):  
Kodi L. Nemunaitis-Berry ◽  
Petra M. Klein ◽  
Jeffrey B. Basara ◽  
Evgeni Fedorovich
Keyword(s):  
Climate Models ◽  
Wrf Model ◽  
Single Layer ◽  
Urban Canopy ◽  
Heat Fluxes ◽  
Urban Air ◽  
Near Surface ◽  
Air Temperatures ◽  
Oklahoma Mesonet ◽  
Joint Urban 2003 Experiment

AbstractAs NWP and climate models continue to evolve toward finer grid spacing, efforts have been undertaken to better represent urban effects. For this study, the single-layer urban canopy model (SLUCM) of the High-Resolution Land Data Assimilation System (HRLDAS) and WRF Model was used to investigate the sensitivity of near-surface air temperatures and energy fluxes to SLUCM parameters in uncoupled (land) and coupled (land–atmosphere) predictions. Output from HRLDAS and WRF was compared with observations from the Oklahoma Mesonet and Joint Urban 2003 experiment. Variations in roof albedo (0.04–0.4) produced 40–135 W m−2 changes in net radiation and sensible heat fluxes. Sensible and ground heat fluxes varied by 40–100 W m−2 with changes in roof thermal conductivity (0.05–1.4). The urban fraction was found to be the only SLUCM parameter to significantly impact latent heat fluxes. Near-surface air temperatures, particularly during the daytime, did not show significant variations with SLUCM parameters (remaining within the 0.5-K range). Differences in urban air temperatures due to the change in boundary layer scheme were greater than the temperature changes due to SLUCM parameter variations. The sensitivity of near-surface air temperatures to SLUCM parameters depended on the method used to calculate the skin temperature of the impervious surface. For all simulations, predicted 2-m urban air temperatures were consistently higher than observations, with deviations approaching 8 K during the day and below 3 K at night. These large errors affected the model’s skill in reproducing the diurnal cycle of UHI intensity.

scholarly journals Impacts of High-Resolution Urban Canopy Parameters within the WRF Model on Dynamical and Thermal Fields over Guangzhou, China

2019 ◽  
Vol 58 (5) ◽  
pp. 1155-1176
Author(s):  
Chong Shen ◽  
Xiaoyang Chen ◽  
Wei Dai ◽  
Xiaohui Li ◽  
Jie Wu ◽  
...  
Keyword(s):  
Heat Flux ◽  
Wind Speed ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Urban Canopy ◽  
Urban Morphology ◽  
Meteorological Model ◽  
Thermal Fields ◽  
Ground Heat Flux ◽  
Surface Skin Temperature

AbstractOn urban scales, the detailed characteristics of land-use information and building properties are vital to improving the meteorological model. The WRF Model with high-spatial-resolution urban fraction (UF) and urban morphology (UM) is used to study the impacts of these urban canopy parameters (UCPs) on dynamical and thermal meteorological fields in two representative seasons in Guangzhou. The results of two seasons are similar and as follows. 1) The impacts of updated UF and UM are obvious on wind speed but minor on temperature and humidity. In the urban environment, the results with updated UF and UM are more consistent with observations compared with the default UCPs, which means the performance of the model has been improved. 2) The dynamical factors associated with wind speed are analyzed. Turbulent kinetic energy (TKE) is significantly affected by UM but little by UF. And both UF and UM are found to influence friction velocity U*. The UM and greater UF attained larger U*. 3) In addition, the thermal fields are analyzed. The UM and increased UF induce higher surface skin temperature (TSK) and ground heat flux in the daytime, indicating that more heat is transported from the surface to the soil. At night, more heat is transported from the soil to the surface, producing higher TSK. For sensible heat flux (HFX), greater UF induces larger HFX during the daytime. But the effects of UM are complex, which makes HFX decrease during the daytime and increase at night. Finally, larger UF attains lower latent heat in the daytime.

scholarly journals The urban fingerprint in the sea-breeze hodograph reveled by high resolution WRF simulations.

2021 ◽  
Author(s):  
David Avisar ◽  
Ran Pelta ◽  
Alexandra Chudnovsky ◽  
Dorita Rostkier-Edelstein
Keyword(s):  
Wrf Model ◽  
Single Layer ◽  
Urban Canopy ◽  
Sea Breeze ◽  
Building Energy ◽  
Weather Research And Forecasting ◽  
Diurnal Cycles ◽  
Convergence Line ◽  
Urban Heat ◽  
First Time

<p>We implement and verify for the first time four Weather Research and Forecasting (WRF) model urban configurations, focused on the coastal metropolitan area of Tel-Aviv (MTA) using updated land use and urban morphological maps. We analyze the mesoscale summertime flow and the urban canopy (UC) role in the occurrence of different hodograph dynamics observed within MTA at night. These events may be significant in the context of air quality research. The four configurations – bulk (MM), single-layer (SLUCM), multi-layer (BEP), and BEP coupled with the building energy model (BEPBEM) – reproduce the observed diurnal temperature and wind diurnal cycles, with similar 10m wind direction bias and RMSE (15° and ~30°, respectively), with preference for MM and SLUCM at night. However, the SLUCM shows the lowest skill for the 10m wind speed (WS) (bias and RMSE equal or larger than 1ms-1), and the BEP shows the largest underestimation of the 2m temperature, ~-2.5°C. In the SLUCM, the WS increases over an UC region and with increasing building heights. The simulations show that at night, a convergence line (CL) builds up with the urban heat island, downstream of the NW flow. West of the CL, the wind continues flowing from the sea, and rotates anti-clockwise to form a non-elliptical sea-breeze hodograph. Removing MTA UC restores an elliptical hodograph. East of the CL, the UC supports an elliptical hodograph with a clockwise rotation through the NE sector, previously reported as dynamically unstable. We expect such wind hodograph dynamics within similar coastal metropolitan areas.</p>

scholarly journals URBAN MICRO CLIMATE MODELLING USING DIFFERENT URBAN PHYISCS SCHEMES AND HIGH RESOLUTION LULC WITH WRF MODEL

2018 ◽  
Vol XLII-5 ◽  
pp. 491-498 ◽  
Author(s):  
M. Bhavana ◽  
K. Gupta ◽  
P. K. Pal
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Relative Humidity ◽  
Wrf Model ◽  
Urban Canopy ◽  
Building Energy ◽  
Urban Morphology ◽  
Urban Land Use ◽  
Single Class ◽  
Ground Observation

<p><strong>Abstract.</strong> Urban areas are treated as a single entity by mesoscale urban canopy models (UCM) for assessing the influence of urban morphology on climate. Weather Research and Forecasting Model (WRF) coupled with UCM along with urban physics options to describe the urban features such as Single Layer Urban Canopy Model (SLUCM), Building Energy Parameterization (BEP) and Building Energy Model (BEM) which enumerates the influence of urban features on the local scale other than the bulk parameterization (no urban physics option), which is generally used in most of the operational forecasting models. Besides, WRF model also enables to integrate multi-class Urban Land Use Land Cover (LULC) whereas most of the globally available LULC depict urban area as single urban built-up class. This study aims to analyze performance of high resolution urban LULC and urban physics options for Chandigarh area by downscaling climatic variables up to 1km and its validation with the ground observation data. The inner domain (1<span class="thinspace"></span>km resolution) was configured with default LULC for one set of simulations and multi-class urban LULC for other set of simulations. All the simulations were carried out for 3 days (August 19&amp;ndash;21, 2017) due to computational restrictions by employing all the four urban physics options. It has been found that multi-class urban LULC yielded better results than single class urban built –up simulation when validated with respect to ground observation. The RMSE values for multi-class urban LULC provided less RMSE than single class urban LULC, those are in terms of temperature at 2<span class="thinspace"></span>m, relative humidity and wind speed are 0.91<span class="thinspace"></span>&amp;deg;C, 2.63% and 1.82<span class="thinspace"></span>m/s respectively. Similarly, BEP+BEM urban physics option provided reduced RMSE values than the SLUCM and BEP scheme. The RMSE values in terms of temperature at 2<span class="thinspace"></span>m, relative humidity and wind speed are 1.11<span class="thinspace"></span>&amp;deg;C, 4.39% and 2.62<span class="thinspace"></span>m/s respectively.</p>

scholarly journals ANALYSIS OF AN EXTRATROPICAL CYCLONE IN THE SOUTHWEST ATLANTIC: WRF MODEL BOUNDARY CONDITIONS SENSITIVITY

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 107-112
Author(s):  
L. R. Diaz ◽  
R. A. Mollmann Junior ◽  
G. B. Muchow ◽  
P. S. Käfer ◽  
N. S. Rocha ◽  
...  
Keyword(s):  
Wind Speed ◽  
Boundary Conditions ◽  
Correlation Coefficient ◽  
Wrf Model ◽  
Reanalysis Data ◽  
Meteorological Conditions ◽  
Extratropical Cyclone ◽  
Superior Performance ◽  
Brazilian Coast ◽  
Southwest Atlantic

Abstract. Meteorological conditions characterize the southern Brazilian coast a cyclogenetic area. The current study seeks to analyse the sensitivity of the WRF model to initial and boundary meteorological conditions in the simulation of an extratropical cyclone that occurred on the southern Brazilian coast on October 28, 2018. For this purpose, the WRF model was set up for two experimental simulations using the NCEP FNL and the NCEP CFSv2 reanalysis data as initial/boundary conditions. The sensitivity analysis was carried out with the cyclone trajectory assessment and comparison with wind speed data from meteorological stations. The results show that the initial meteorological conditions significantly influence the simulation of the cyclone track. In a nutshell, the use of NCEP CFSv2 resulted in more accurate wind speed simulations when compared to the values observed in the stations. With correlation coefficient values around 0.7, and the lowest bias (−2.57 m/s) and RMSE (3.68 m/s). In contrast, using the NCEP FNL data, the lowest correlation coefficient and the highest bias and RMSE values were obtained: 0.58, −3.97 m/s and 4.91 m/s, respectively. However, both simulations tend to underestimate observational wind speed values. The superior performance of simulations using CFSv2 tends to be related to the finer horizontal resolution of this reanalysis data source.

Statistical characteristics of the morphological parameters of Chinese cities and the application in WRF model

2020 ◽  
Author(s):  
Ning Zhang
Keyword(s):  
Urban Areas ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Urban Canopy ◽  
Urban Heat Islands ◽  
Statistical Characteristics ◽  
Morphological Parameters ◽  
Area Index ◽  
Chinese Cities ◽  
Building Height

&lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;div&gt; &lt;p&gt;With ever-increasing urban populations, cities face a serious of climatic and environmental issues such as urban heat islands (UHIs), air pollution and extreme weather. Urban morphological parameters can improve the performance of WRF model in urban areas. A 3-D urban canopy parameters (UCPs) are calculated for the 62 major cities in China.Chinese cities could be divided into two types (single_peak and double_peak) based on the distribution of building height, and the two peaks are located at level 2 (about 5m) and level 6 (about 20m). The mean number of buildings in single_peak city is much larger than that of double_peak.The building height of double_peak cities is larger than that of single_peak cities, but the building plan area fraction, building surface area to plan area ratio and frontal area index are opposite. The WRF default setting underestimates the street width but overestimates the building width of Chinese cities. The UCPs improve the simulation of nocturnal 2-m surface air temperature and 10-m wind speed in the testing cases.&lt;/p&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt; &lt;/div&gt;

scholarly journals Assessing the Impact of Enhanced Hydrological Processes on Urban Hydrometeorology with Application to Two Cities in Contrasting Climates

2016 ◽  
Vol 17 (4) ◽  
pp. 1031-1047 ◽  
Author(s):  
Jiachuan Yang ◽  
Zhi-Hua Wang ◽  
Matei Georgescu ◽  
Fei Chen ◽  
Mukul Tewari
Keyword(s):  
Water Cycle ◽  
Wrf Model ◽  
Single Layer ◽  
Urban Canopy ◽  
Field Measurements ◽  
Green Roofs ◽  
The United States ◽  
Climatic Conditions ◽  
Hydrological Processes ◽  
The Impact

Abstract To enhance the capability of models in better characterizing the urban water cycle, physical parameterizations of urban hydrological processes have been implemented into the single-layer urban canopy model in the widely used Weather Research and Forecasting (WRF) Model. While the new model has been evaluated offline against field measurements at various cities, its performance in online settings via coupling to atmospheric dynamics requires further examination. In this study, the impact of urban hydrological processes on regional hydrometeorology of the fully integrated WRF–urban modeling system for two major cities in the United States, namely, Phoenix and Houston, is assessed. Results show that including hydrological processes improves prediction of the 2-m dewpoint temperature, an indicative measure of coupled thermal and hydrological processes. The implementation of green roof systems as an urban mitigation strategy is then tested at the annual scale. The reduction of environmental temperature and increase of humidity by green roofs indicate strong diurnal and seasonal variations and are significantly affected by geographical and climatic conditions. Comparison with offline studies reveals that land–atmosphere interactions play a crucial role in determining the effect of green roofs.

scholarly journals Enhancing Wind Turbine Power Forecast via Convolutional Neural Network

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 261
Author(s):  
Tianyang Liu ◽  
Zunkai Huang ◽  
Li Tian ◽  
Yongxin Zhu ◽  
Hui Wang ◽  
...  
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Wind Turbine ◽  
Wind Power ◽  
Rapid Development ◽  
Superior Performance ◽  
Learning Platform ◽  
Novel Approach ◽  
Wind Power Forecast ◽  
Transformation Methods

The rapid development in wind power comes with new technical challenges. Reliable and accurate wind power forecast is of considerable significance to the electricity system’s daily dispatching and production. Traditional forecast methods usually utilize wind speed and turbine parameters as the model inputs. However, they are not sufficient to account for complex weather variability and the various wind turbine features in the real world. Inspired by the excellent performance of convolutional neural networks (CNN) in computer vision, we propose a novel approach to predicting short-term wind power by converting time series into images and exploit a CNN to analyze them. In our approach, we first propose two transformation methods to map wind speed and precipitation data time series into image matrices. After integrating multi-dimensional information and extracting features, we design a novel CNN framework to forecast 24-h wind turbine power. Our method is implemented on the Keras deep learning platform and tested on 10 sets of 3-year wind turbine data from Hangzhou, China. The superior performance of the proposed method is demonstrated through comparisons using state-of-the-art techniques in wind turbine power forecasting.

Interpretation of Atmospheric CO2 Measurements in Mexico City

2021 ◽  
Author(s):  
Yang Xu ◽  
Michel Ramonet ◽  
Thomas Lauvaux ◽  
Jinghui Lian ◽  
Francois-Marie Bréon ◽  
...  
Keyword(s):  
Mexico City ◽  
Rural Areas ◽  
Ghg Emissions ◽  
Single Layer ◽  
Urban Canopy ◽  
Horizontal Resolution ◽  
Complex Topography ◽  
Urban Station ◽  
Mountain Areas ◽  
Mixing Ratios

&lt;p&gt;The French-Mexican project Mexico City&amp;#8217;s Regional Carbon Impacts (MERCI-CO&lt;sub&gt;2&lt;/sub&gt;) is building a CO&lt;sub&gt;2&lt;/sub&gt; observation network in the Metropolitan Zone of the Valley of Mexico (ZMVM). The project investigates the atmospheric signals generated by the city's emissions on total column and surface measurements, aiming at reducing the uncertainties of CO&lt;sub&gt;2&lt;/sub&gt; emissions in ZMVM and evaluating the effects of policies that had been implemented by the city authorities.&amp;#160;&lt;/p&gt;&lt;p&gt;A nested high-resolution atmospheric transport simulation based on the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) is performed to analyze the observed CO&lt;sub&gt;2&lt;/sub&gt; mixing ratios during dry and wet seasons over Mexico City and its vicinity. Both anthropogenic emissions (UNAM 1-km fossil fuel emissions) and biogenic fluxes (CASA 5-km simulations) are taken into account. The model configuration, with a horizontal resolution of 1km and using the Single-Layer urban canopy Model (SLUCM), has been evaluated over two weeks in January 2018 using meteorological measurements from 26 stations set by the Air Quality Agency of Mexico City (Secretary of the Environment of Mexico City - SEDEMA). The reconstruction of meteorological conditions in the urban area shows better performances than suburban and mountainous areas. Due to the complex topography, wind speeds in mountain areas are 2-3 m/s over estimated and wind direction simulations in some stations are 90&amp;#176; deflected, especially in southern mountains.&amp;#160;&lt;/p&gt;&lt;p&gt;Two high-precision CO&lt;sub&gt;2&lt;/sub&gt; analyzers deployed in urban and rural areas of Mexico City are used to evaluate the WRF CO&lt;sub&gt;2&lt;/sub&gt; 1-km simulations. The model reproduced the diurnal cycle of CO&lt;sub&gt;2&lt;/sub&gt; mixing ratios at the background station but under-estimates the nighttime accumulation at the urban station. Mean absolute errors of CO&lt;sub&gt;2&lt;/sub&gt; concentrations range from 6.5 ppm (background station) to 27.1 ppm (urban station), mostly driven by the elevated nocturnal enhancements (up to 500 ppm at UNAM station). Based on this analysis, we demonstrate the challenges and potential of mesoscale modeling over complex topography, and the potential use of mid-cost sensors to constrain the urban GHG emissions of Mexico City.&lt;/p&gt;

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