A comparison between WRF-simulated and observed surface meteorological variables across varying land cover and urbanization in south-central India

Kadaverugu, Rakesh

doi:10.1007/s12145-022-00927-z

Cited by 7 publications

(3 citation statements)

References 51 publications

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“…The resolution of the WRF simulation in this study was 3 × 3 km, but the input data was 1 × 1 km, which might have caused errors in the simulation results [50]. In comparison with analyses based on station data and reanalysis information, simulation experiments have the advantage of wide spatial coverage and good data coincidence [51]. In this study, the climatic effects of elevated levels of atmospheric CO 2 concentration were studied by comparing and analyzing the differences between the simulations; consequently, systematic errors do not affect the validity of the results.…”

Section: Discussionmentioning

confidence: 94%

Simulation Study on the Effect of Elevated CO2 on Regional Temperature Change on the Loess Plateau

et al. 2023

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CO2 undisputedly affects global temperature change, but the specific impact of change in atmospheric CO2 concentration on regional warming remains to be quantified, especially in different climatic backgrounds. Taking the Loess Plateau as the research area, this study quantified the effect of CO2 elevation on regional temperature change based on a single-factor sensitivity experiment of the regional Weather Research and Forecasting (WRF) climatic model, and the results revealed the following: (i) The correlation coefficient between monthly mean values of temperature simulated by the WRF model and the observed values reached 0.96 (p < 0.01), and the overall spatial trends of simulated and observed temperatures increased from the northwest to the southeast. (ii) CO2 concentration increased from 370.70 ppm in 2000 to 414.54 ppm in 2020, and the Loess Plateau region warmed by 0.04 and 0.06 °C under the MODIS land cover of 2000 and 2020, respectively. This indicates that increase in CO2 concentration over the Loess Plateau has greater impact than land cover change on regional temperature change. (iii) As CO2 concentration increased, the maximum fluctuation of temperature in summer exceeded 2.0 °C, while the fluctuations in spring (0.72 °C), autumn (0.77 °C), and winter (0.15 °C) were relatively small, indicating that summer temperature is most sensitive to CO2 concentration change. By emphasizing the marked temperature difference associated with the same CO2 change in different seasons, this study provides an important basis for extending the understanding of the differences in the effect of CO2 on regional temperatures.

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Section: Discussionmentioning

confidence: 94%

Simulation Study on the Effect of Elevated CO2 on Regional Temperature Change on the Loess Plateau

et al. 2023

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“…The physical model method aims to construct mathematical equations based on physical principles and has become an important method for obtaining remote sensing data products [19]. The widely used physical model methods include the surface energy balance method and its derivatives [20,21], which can provide data that are as close to the true values as possible. However, there is often high uncertainty due to the difficulty in determining certain parameters.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Reconstructed All-Weather Land Surface Temperature for Urban Heat Island Analysis

Zhang,

Meng,

Gou

et al. 2024

Remote Sensing

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With the continuous improvement of urbanization levels in the Lhasa area, the urban heat island effect (UHI) has seriously affected the ecological environment of the region. However, the satellite-based thermal infrared land surface temperature (LST), commonly used for UHI research, is affected by cloudy weather, resulting in a lack of continuous spatial and temporal information. In this study, focusing on the Lhasa region, we combine simulated LST data obtained by the Weather Research and Forecasting (WRF) model with remote sensing-based LST data to reconstruct the all-weather LST for March, June, September, and December of 2020 at a resolution of 0.01° while using the Moderate-Resolution Imaging Spectroradiometer (MODIS) LST as a reference (in terms of accuracy). Subsequently, based on the reconstructed LST, an analysis of the UHI was conducted to obtain the spatiotemporal distribution of UHI in the Lhasa region under all-weather LST conditions. The results demonstrate that the reconstructed LST effectively captures the expected spatial distribution characteristics with high accuracy, with an average root mean square error of 2.20 K, an average mean absolute error of 1.51 K, and a correlation coefficient consistently higher than 0.9. Additionally, the heat island effect in the Lhasa region is primarily observed during the spring and winter seasons, with the heat island intensity remaining relatively stable in winter. The results of this study provide a new reference method for the reconstruction of all-weather LST, thereby improving the research accuracy of urban thermal environment from the perspective of foundational data. Additionally, it offers a theoretical basis for the governance of UHI in the Lhasa region.

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“…This drastic rise in urban expansion and associated land use and land cover (LULC) changes may lead to a rise in land surface temperature (LST) over urban regions, which in turn leads to the development of extreme urban heat island (UHI) zones over cities. Some early studies, such as (Kadaverugu, 2023;Sultana & Satyanarayana, 2023), have reported urban impacts of UHI and surface energy exchanges and analyzed basic meteorological variables over urban regions. These UHI zones will significantly impact outdoor thermal comfort (Ren et al, 2023) and the elevated temperatures in urban set-up, resulting in significant health issues (Chen & Ng, 2012;Jiang et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Universal Thermal Comfort Index (UTCI) using the WRF-UCM model over a Metropolitan City in India

Peri,

Satyanarayana

2023

Preprint

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Rapid urbanization leads to an increase in urban air temperature, considerably affecting health, comfort and the quality of life in urban spaces. The accurate assessment of outdoor thermal comfort is crucial for urban health. In the present study, a high-resolution mesoscale model coupled with a layer Urban Canopy Model (WRF-UCM) is implemented over the city of Hyderabad (17.3850° N, 78.4867° E) to simulate urban meteorological conditions during the summer and winter period of 2009 and 2019. The universal thermal climate index (UTCI) has been estimated using the model-derived atmospheric variables and a human biometeorology parameter to assess the linkages between the outdoor environment and thermal comfort. Results revealed that during summer, the city experiences nearly 10 hours of extreme to strong thermal stress, whereas moderate thermal and slight cold stress are experienced during winter. The urban area in Hyderabad expanded from 5–15% during the study period, leading to a 3℃ (1.5 ℃) increase in land surface temperature and a 1 to 1.5 ℃ (0.5 to 1 ℃ ) rise in air temperature at 2m height and UTCI during summer (winter) time. The analysis reveals that the maximum UTCI values were noticed over built-up areas compared to other land classes during daytime as well as nighttime. The results derived from the present study have shown the performance of WRF-UCM-derived UTCI reasonably portrayed the significant impact of urbanization on thermal comfort over the city and provided useful insights with regard to urban comfort and welfare.

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A comparison between WRF-simulated and observed surface meteorological variables across varying land cover and urbanization in south-central India

Cited by 7 publications

References 51 publications

Simulation Study on the Effect of Elevated CO2 on Regional Temperature Change on the Loess Plateau

Simulation Study on the Effect of Elevated CO2 on Regional Temperature Change on the Loess Plateau

Evaluating the Reconstructed All-Weather Land Surface Temperature for Urban Heat Island Analysis

Assessment of Universal Thermal Comfort Index (UTCI) using the WRF-UCM model over a Metropolitan City in India

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