A New Land-Use Dataset for the Weather Research and Forecasting (WRF) Model

The USGS (United States Geological Survey) land-use data used in the Weather Research and Forecasting (WRF) model have become obsolete as they are unable to accurately represent actual underlying surface features. Therefore, this study developed a new multi-satellite remote-sensing land-use dataset based on the latest GLC2015 (Global Land Cover, 2015) land-use data, which had 300 m spatial resolution. The new data were used to update the default USGS land-use dataset. Based on observational data from national meteorological observing stations in Xinjiang, northwest China, a comparison of the old USGS and new GLC2015 land-use datasets in the WRF model was performed for July 2018, where the simulated variables included the sensible heat flux (SHF), latent heat flux (LHF), surface skin temperature (Tsk), two-meter air temperature (T2), wind speed (Winds), specific humidity (Q2) and relative humidity (RH). The results indicated that there were significant differences between the two datasets. For example, our statistical verification results found via in situ observations made by the MET (model evaluation tools) illustrated that the bias of T2 decreased by 2.54%, the root mean square error (RMSE) decreased by 1.48%, the bias of Winds decreased by 10.46%, and the RMSE decreased by 6.77% when using the new dataset, and the new parameter values performed a net positive effect on land–atmosphere interactions. These results suggested that the GLC2015 land-use dataset developed in this study was useful in terms of improving the performance of the WRF model in the summer months.

Download Full-text

The efficiency of the Weather Research and Forecasting (WRF) model for simulating typhoons

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-2179-2014 ◽

2014 ◽

Vol 14 (8) ◽

pp. 2179-2187 ◽

Cited By ~ 4

Author(s):

T. Haghroosta ◽

W. R. Ismail ◽

P. Ghafarian ◽

S. M. Barekati

Keyword(s):

Heat Flux ◽

Wind Speed ◽

Model Simulation ◽

Sensible Heat Flux ◽

Wrf Model ◽

Heat Fluxes ◽

Weather Research And Forecasting ◽

Data Set ◽

Wind Speed Prediction ◽

Weather Research

Abstract. The Weather Research and Forecasting (WRF) model includes various configuration options related to physics parameters, which can affect the performance of the model. In this study, numerical experiments were conducted to determine the best combination of physics parameterization schemes for the simulation of sea surface temperatures, latent heat flux, sensible heat flux, precipitation rate, and wind speed that characterized typhoons. Through these experiments, several physics parameterization options within the Weather Research and Forecasting (WRF) model were exhaustively tested for typhoon Noul, which originated in the South China Sea in November 2008. The model domain consisted of one coarse domain and one nested domain. The resolution of the coarse domain was 30 km, and that of the nested domain was 10 km. In this study, model simulation results were compared with the Climate Forecast System Reanalysis (CFSR) data set. Comparisons between predicted and control data were made through the use of standard statistical measurements. The results facilitated the determination of the best combination of options suitable for predicting each physics parameter. Then, the suggested best combinations were examined for seven other typhoons and the solutions were confirmed. Finally, the best combination was compared with other introduced combinations for wind-speed prediction for typhoon Washi in 2011. The contribution of this study is to have attention to the heat fluxes besides the other parameters. The outcomes showed that the suggested combinations are comparable with the ones in the literature.

Download Full-text

Understanding land use change impacts on microclimate using Weather Research and Forecasting (WRF) model

Physics and Chemistry of the Earth Parts A/B/C ◽

10.1016/j.pce.2017.01.017 ◽

2018 ◽

Vol 103 ◽

pp. 115-126 ◽

Cited By ~ 13

Author(s):

Xia Li ◽

Chandana Mitra ◽

Li Dong ◽

Qichun Yang

Keyword(s):

Land Use ◽

Land Use Change ◽

Wrf Model ◽

Weather Research And Forecasting ◽

Weather Research

Download Full-text

Numerical Evaluation of the Impact of Urbanization on Summertime Precipitation in Osaka, Japan

Advances in Meteorology ◽

10.1155/2015/379361 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 13

Author(s):

Hikari Shimadera ◽

Akira Kondo ◽

Kundan Lal Shrestha ◽

Ken Kitaoka ◽

Yoshio Inoue

Keyword(s):

Land Use ◽

Heat Flux ◽

Urban Areas ◽

Sensible Heat Flux ◽

Wrf Model ◽

Temporal Distribution ◽

Urban Land Use ◽

Sensible Heat ◽

Impact Of Urbanization ◽

The Impact

This study utilized the Weather Research and Forecasting (WRF) model version 3.5.1 to evaluate the impact of urbanization on summertime precipitation in Osaka, Japan. The evaluation was conducted by comparing the WRF simulations with the present land use and no-urban land use (replacing “Urban” with “Paddy”) for August from 2006 to 2010. The urbanization increased mean air temperature by 2.1°C in urban areas because of increased sensible heat flux and decreased mean humidity by 0.8 g kg−1because of decreased latent heat flux. In addition, the urbanization increased duration of the southwesterly sea breeze. The urbanization increased precipitation in urban areas and decreased in the surrounding areas. The mean precipitation in urban areas was increased by 20 mm month−1(27% of the total amount without the synoptic-scale precipitation). The precipitation increase was generally due to the enhancement of the formation and development of convective clouds by the increase in sensible heat flux during afternoon and evening time periods. The urbanization in Osaka changes spatial and temporal distribution patterns of precipitation and evaporation, and consequently it substantially affects the water cycle in and around the urban areas of Osaka.

Download Full-text

The Impacts of Soil Moisture Initialization on the Forecasts of Weather Research and Forecasting Model: A Case Study in Xinjiang, China

Water ◽

10.3390/w12071892 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1892

Author(s):

Hailiang Zhang ◽

Junjian Liu ◽

Huoqing Li ◽

Xianyong Meng ◽

Ablimitijan Ablikim

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Weather Prediction ◽

Potential Temperature ◽

Wrf Model ◽

Specific Humidity ◽

Water Evaporation ◽

Weather Research And Forecasting ◽

Soil Moisture Initialization ◽

Weather Research

Soil moisture is a critical parameter in numerical weather prediction (NWP) models because it plays a fundamental role in the exchange of water and energy cycles between the atmosphere and the land surface through evaporation. To improve the forecast skills of the Weather Research and Forecasting (WRF) model in Xinjiang, China, this study investigated the impacts of soil moisture initialization on the WRF forecasts by performing a series of simulations. A group of simulations was conducted using the single-column model (SCM) from 1200 UTC on 15 to 18 August 2019, at Urumchi, Xinjiang (43.78° N, 87.6° E); another was performed using the WRF model for a real weather case in Xinjiang from 0000 UTC 15 August to 1200 UTC 18 August 2019, which included an episode of heavy precipitation and gales. Our most notable findings are as follows. Specific humidity increases and potential temperature decreases persistently when soil moisture increases because of soil water evaporation. Soil moisture initialization could impact the energy budget and modulate the partition of the total available energy at the land surface significantly through evaporation and the greenhouse effect. Replacing the soil moisture with a proper multiple of the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) soil moisture data could significantly improve the critical success index (CSI) and frequency bias (FBIAS) of precipitation and the root-mean-squared errors (RMSEs) of 2-m specific humidity and 2-m temperature. These findings indicate the prospect of a new way to improve the forecast skills of WRF in Xinjiang or other similar regions.

Download Full-text

Investigating the Effect of Urbanization on Weather Using the Weather Research and Forecasting (WRF) Model: A Case of Metro Manila, Philippines

Environments ◽

10.3390/environments6020010 ◽

2019 ◽

Vol 6 (2) ◽

pp. 10 ◽

Cited By ~ 2

Author(s):

Jervie Oliveros ◽

Edgar Vallar ◽

Maria Galvez

Keyword(s):

Heat Flux ◽

Rural Areas ◽

Sensible Heat Flux ◽

Maximum Temperature ◽

Weather Research And Forecasting ◽

Trend Test ◽

Sensible Heat ◽

Metro Manila ◽

Urban And Rural Areas ◽

Weather Research

The effect of urbanization of Metro Manila, particularly on the amount of sensible heat flux, rainfall and temperature of selected urban and rural areas, was investigated using the Weather Research and Forecasting Version 3.4.1 (WRFV3.4.1) model. National Center for Environmental Prediction - Final (NCEP-FNL) grib1 data from 2000 to 2010 were used as inputs into the model for meteorological data. The Mann–Kendall trend test (M–K test) was utilized to verify the significance of the trends while Sen’s slope estimator was used to quantify the measured trends. Results showed that, on average, the sensible heat flux of Metro Manila is about 1.5 × 108 Jm−2 higher than in selected areas outside Metro Manila. The occurrence of an urban heat island (UHI) effect was detected in Metro Manila by comparing the difference in the minimum and maximum temperatures. For the selected urban and rural areas, the minimum and maximum temperature differences (relative to Metro Manila) are around 0.4 to 2.4 °C and 0.83 to 2.3 °C, respectively. Metro Manila recorded higher 11-year average values of rainfall during the summer season (8% to 64%), rainy season (15% to 305%), and transition season (8% to 232%) when compared with selected areas from 25 to 100 km from Manila. These results show that the sensible heat flux, temperature and rainfall in Metro Manila is affected by Metro Manila’s urbanization.

Download Full-text

Evaluating the Climate Effects of Reforestation in New England Using a Weather Research and Forecasting (WRF) Model Multiphysics Ensemble

Journal of Climate ◽

10.1175/jcli-d-15-0286.1 ◽

2016 ◽

Vol 29 (14) ◽

pp. 5141-5156 ◽

Cited By ~ 15

Author(s):

E. A. Burakowski ◽

S. V. Ollinger ◽

G. B. Bonan ◽

C. P. Wake ◽

J. E. Dibb ◽

...

Keyword(s):

Heat Flux ◽

New England ◽

Sensible Heat Flux ◽

Climate Impacts ◽

Maximum Temperature ◽

Weather Research And Forecasting ◽

Surface Model ◽

Sensible Heat ◽

Ground Heat Flux ◽

Weather Research

Abstract The New England region of the northeastern United States has a land use history characterized by forest clearing for agriculture and other uses during European colonization and subsequent reforestation following widespread farm abandonment. Despite these broad changes, the potential influence on local and regional climate has received relatively little attention. This study investigated wintertime (December through March) climate impacts of reforestation in New England using a high-resolution (4 km) multiphysics ensemble of the Weather Research and Forecasting Model. In general, the conversion from mid-1800s cropland/grassland to forest led to warming, but results were sensitive to physics parameterizations. The 2-m maximum temperature (T2max) was most sensitive to choice of land surface model, 2-m minimum temperature (T2min) was sensitive to radiation scheme, and all ensemble members simulated precipitation poorly. Reforestation experiments suggest that conversion of mid-1800s cropland/grassland to present-day forest warmed T2max +0.5 to +3 K, with weaker warming during a warm, dry winter compared to a cold, snowy winter. Warmer T2max over forests was primarily the result of increased absorbed shortwave radiation and increased sensible heat flux compared to cropland/grassland. At night, T2min warmed +0.2 to +1.5 K where deciduous broadleaf forest replaced cropland/grassland, a result of decreased ground heat flux. By contrast, T2min of evergreen needleleaf forest cooled –0.5 to –2.1 K, primarily owing to increased ground heat flux and decreased sensible heat flux.

Download Full-text

Land-Use Improvements in the Weather Research and Forecasting Model over Complex Mountainous Terrain and Comparison of Different Grid Sizes

Boundary-Layer Meteorology ◽

10.1007/s10546-021-00617-1 ◽

2021 ◽

Author(s):

Alessio Golzio ◽

Silvia Ferrarese ◽

Claudio Cassardo ◽

Gugliemina Adele Diolaiuti ◽

Manuela Pelfini

Keyword(s):

Boundary Layer ◽

Land Use ◽

Land Cover ◽

Mixing Layer ◽

Local Area ◽

Heat Fluxes ◽

Weather Research And Forecasting ◽

Forecasting Model ◽

Mountainous Terrain ◽

Weather Research

AbstractWeather forecasts over mountainous terrain are challenging due to the complex topography that is necessarily smoothed by actual local-area models. As complex mountainous territories represent 20% of the Earth’s surface, accurate forecasts and the numerical resolution of the interaction between the surface and the atmospheric boundary layer are crucial. We present an assessment of the Weather Research and Forecasting model with two different grid spacings (1 km and 0.5 km), using two topography datasets (NASA Shuttle Radar Topography Mission and Global Multi-resolution Terrain Elevation Data 2010, digital elevation models) and four land-cover-description datasets (Corine Land Cover, U.S. Geological Survey land-use, MODIS30 and MODIS15, Moderate Resolution Imaging Spectroradiometer land-use). We investigate the Ortles Cevadale region in the Rhaetian Alps (central Italian Alps), focusing on the upper Forni Glacier proglacial area, where a micrometeorological station operated from 28 August to 11 September 2017. The simulation outputs are compared with observations at this micrometeorological station and four other weather stations distributed around the Forni Glacier with respect to the latent heat, sensible heat and ground heat fluxes, mixing-layer height, soil moisture, 2-m air temperature, and 10-m wind speed. The different model runs make it possible to isolate the contributions of land use, topography, grid spacing, and boundary-layer parametrizations. Among the considered factors, land use proves to have the most significant impact on results.

Download Full-text