Evaluating the Impacts of Land Cover and Soil Texture Changes on Simulated Surface Wind and Temperature

Abstract

In this study, Chinese Academy of Sciences land cover dataset (CAS_LC) and soil texture dataset (CAS_ST) as well as Tsinghua University land cover dataset (TU_LC) were incorporated into the Weather Research and Forecasting (WRF) model to evaluate the impacts of land cover and soil texture changes on the surface wind and air temperature as compared with outdated default datasets. Six modeling scenarios including single updating for the three new datasets, combined updating of new datasets (CAS_LC + CAS_ST, TU_LC + CAS_ST), and default datasets are designed. WRF simulations were conducted with three resolutions (9, 3, and 1 km) for the period of 14 July to 31 September 2017 over Harbin. Results of the 10-m wind speed, 10-m wind direction, and 2-m air temperature (T2) were evaluated against WRF default datasets (WLS). Results show that TU_LC-related simulations with lower mean absolute error (MAE) demonstrated the usefulness of this dataset in the wind speed simulation, while the changing soil texture exerted a limited effect on modeled wind. CAS_LC improved simulated wind direction and T2. Significant changes in the three variables were frequently induced by urban and built-up land or water bodies related transformations. The 3-km grid resolution was sufficient to reasonably simulate the surface winds and air temperature. The roughness length was a main factor disturbing the wind speed, while the land cover transformation was responsible for the changes in surface temperature and heat fluxes, thereby affecting T2 simulation.

Data-driven model of the local wind field over two small lakes in Jyväskylä, Finland

“…A Laplacian filter is often used to detect edges of the digital image, and we computed second derivatives of the elevation z in DEM (Fig. 2) using the following equation: The effects of surface roughness (or land cover) and topography on wind behavior have been studied, and the importance of these two factors have been reported by many researchers (e.g., Ruel et al 1998;Tian et al 2015;Fu et al 2020). Even though surface roughness and topography parameters were not considered in the modeling, the proposed model can reasonably predict the wind speed and direction over two lakes reasonably.…”

Evaluation of High-Resolution Land Cover Geographical Data for the WRF Model Simulations

“…The process of the reclassification of the CGLS-LC100 classes to MODIS classes is presented in Table 1. To implement stage three, the reclassified LULC CGLS-LC100 data were transformed into binary data [46]. The data format was changed using GDALL [12].…”

“…Most articles on the influence of local conditions on NWP (Numerical Weather Prediction) results focus on the effect of changing LULC on basic parameters such as temperature [38,41,42] and humidity. The subject of wind speed and direction analysis has been addressed less frequently [31,[43][44][45][46][47]. The forecast of wind direction is largely dependent on the conditions of placement of the meteorological station.…”

Tinjauan Pengaruh Perubahan Tutupan Lahan Terhadap Parameter Cuaca

“…Perbandingan hasil simulasi dengan skenario data tutupan lahan MODIS2001 dengan GlobCover2009, menunjukkan pengaruh pada sirkulasi medan angin yang ditimbulkan selama periode Typhoon Tammasun (Yin, et al, 2020). Kekasaran lahan yang berbeda pada perubahan lahan terbangun dan permukaan air, dalam pemodelan numerik cuaca, juga mampu menyebabkan variasi kondisi angin (Fu, et al, 2020). Perubahan lahan dari lahan pertanian dan padang rumput yang menjadi hutan campuran di wilayah Harbin, China menyebabkan perbedaan arah angin mencapai 30⁰, sedangkan wilayah pinggiran kota yang mengalami perubahan perkotaan dan lahan terbangun menjadi lahan pertanian dan padang rumput mengalami penurunan kecepatan angin hingga 0,9 m/s (Fu, et al, 2020).…”