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Volume 15
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10.3390/rs15102686
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Article

Satellite-Based Estimation of Roughness Length over Vegetated Surfaces and Its Utilization in WRF Simulations

by
Yiming Liu
1,2,3,
Chong Shen
4,*,
Xiaoyang Chen
5,6,
Yingying Hong
7,
Qi Fan
1,2,3,
Pakwai Chan
8,
Chunlin Wang
3,4 and
Jing Lan
4
1
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai 519082, China
2
Guangdong Provincial Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary, Guangzhou 510275, China
3
Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
4
Guangzhou Climate and Agrometeorology Center, Guangzhou 511430, China
5
Institute of Tropical and Marine Meteorology, China Meteorological Administration, Guangzhou 510640, China
6
Department of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA
7
Guangdong Ecological Meteorology Center, Guangzhou 510640, China
8
Hong Kong Observatory, Hong Kong 999077, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2023, 15(10), 2686; https://doi.org/10.3390/rs15102686
Submission received: 11 March 2023 / Revised: 8 May 2023 / Accepted: 17 May 2023 / Published: 22 May 2023
(This article belongs to the Section Atmospheric Remote Sensing)
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Abstract

Based on morphological methods, MODIS satellite remote sensing data were used to establish a dataset of the local roughness length (Z0) of vegetation-covered surfaces in Guangdong Province. The local Z0 was used to update the mesoscale Weather Research and Forecasting (WRF) model in order to quantitatively evaluate its impact on the thermodynamic environment of vegetation-covered surfaces. The specific results are as follows: evergreen broad-leaved forests showed the largest average Z0 values at 1.27 m (spring), 1.15 m (summer), 1.03 m (autumn), and 1.15 m (winter); the average Z0 values of mixed forests ranged from 0.90 to 1.20 m; and those for cropland-covered surfaces ranged from 0.17 to 0.20 m. The Z0 values of individual vegetation coverage types all exhibited relatively high values in spring and low values in autumn, and the default Z0 corresponding to specific vegetation-covered surfaces was significantly underestimated in the WRF model. Modifying the default Z0 of surfaces underlying evergreen broad-leaved forests, mixed forests, and croplands in the model induced only relatively small changes (<1%) in their 2 m temperature, relative humidity, skin surface temperature, and the planetary boundary layer height. However, the average daily wind speed of surfaces covered by evergreen broad-leaved forests, mixed forests, and croplands was reduced by 0.48 m/s, 0.43 m/s, and 0.26 m/s, respectively, accounting for changes of 12.0%, 11.1%, and 6.5%, respectively.
Keywords: roughness length; vegetation covered surface; WRF model; Guangdong Province roughness length; vegetation covered surface; WRF model; Guangdong Province
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MDPI and ACS Style

Liu, Y.; Shen, C.; Chen, X.; Hong, Y.; Fan, Q.; Chan, P.; Wang, C.; Lan, J. Satellite-Based Estimation of Roughness Length over Vegetated Surfaces and Its Utilization in WRF Simulations. Remote Sens. 2023, 15, 2686. https://doi.org/10.3390/rs15102686

AMA Style

Liu Y, Shen C, Chen X, Hong Y, Fan Q, Chan P, Wang C, Lan J. Satellite-Based Estimation of Roughness Length over Vegetated Surfaces and Its Utilization in WRF Simulations. Remote Sensing. 2023; 15(10):2686. https://doi.org/10.3390/rs15102686

Chicago/Turabian Style

Liu, Yiming, Chong Shen, Xiaoyang Chen, Yingying Hong, Qi Fan, Pakwai Chan, Chunlin Wang, and Jing Lan. 2023. "Satellite-Based Estimation of Roughness Length over Vegetated Surfaces and Its Utilization in WRF Simulations" Remote Sensing 15, no. 10: 2686. https://doi.org/10.3390/rs15102686

APA Style

Liu, Y., Shen, C., Chen, X., Hong, Y., Fan, Q., Chan, P., Wang, C., & Lan, J. (2023). Satellite-Based Estimation of Roughness Length over Vegetated Surfaces and Its Utilization in WRF Simulations. Remote Sensing, 15(10), 2686. https://doi.org/10.3390/rs15102686

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