Abstract
Changes in land use and land cover (LULC) and urbanization affect the regional energy balance. Accurate estimation of the earth's surface skin temperature and surface thermodynamic variables (temperature, T and relative humidity, RH) is essential to understand regional climate change better. The present study examined the agreeability between the Weather Research and Forecasting (WRF) model simulated surface skin temperature (TSK) and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-derived land surface temperature (LST) over heterogeneous LULC (built-up, crop land, forest cover, and barren land) in south-central India. Model performance metrics were computed for daytime and nighttime surface temperatures in January, May, and July 2021, representing winter, summer, and monsoon seasons. Further, the study compared the WRF-simulated near-surface (2 m from surface) T and RH with the observed hourly data from 20 locations in south-central India representing Tier-I, Tier-II, and Tier-III cities (high to low urbanization) to understand the effect of urbanization. Results indicate an overall high correlation (r > 0.9) between WRF-TSK and MODIS-LST. Nighttime correlations (r > 0.55) are relatively good enough for crop and forest land-use group than daytime simulations. In general, the correlation between TSK and LST is relatively poor for barren and built-up land-use groups during all three seasons (for both daytime and nighttime). Similarly, the WRF-simulated T and RH also differ considerably from the observed data in high and moderately dense urban locations, and the seasonal biases are predominant, especially during summer and winter. The WRF-simulated surface variables are a reasonable alternative in the absence of satellite-observed or surface-measured data in better understanding the environmental processes. However, the trends in the surface meteorological variables needs to be interpreted by duly considering the impact of land use and urbanization.
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Data availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- CPCB:
-
Central pollution control board
- DEM:
-
Digital elevation model
- GEE:
-
Google earth engine
- LST:
-
Land surface temperature
- LULC:
-
Land use and land cover
- MODIS:
-
Moderate resolution imaging spectroradiometer
- PBL:
-
Planetary boundary layer
- RH-2m:
-
Near-surface relative humidity at 2 m height
- RMSE:
-
Root mean square error
- T-2m:
-
Near-surface air temperature at 2 m height
- TSK:
-
Surface skin temperature
- UCI:
-
Urban cool island
- UCM:
-
Urban canopy model
- UHI:
-
Urban heat island
- WPS:
-
WRF pre-processing system
- WRF:
-
Weather research and forecasting model
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Acknowledgements
The author acknowledges the data providers NCEP FNL, CPCB, and GEE. The Knowledge Resources Center (KRC) of CSIR National Environmental Engineering Research Institute (NEERI) is helpful in checking the similarity of the manuscript — CSIR-NEERI/KRC/2022/MAY/CTMD/3. The author is grateful to Ms. Arya and Ms. Astha for downloading the CPCB meteorological data.
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Kadaverugu, R. A comparison between WRF-simulated and observed surface meteorological variables across varying land cover and urbanization in south-central India. Earth Sci Inform 16, 147–163 (2023). https://doi.org/10.1007/s12145-022-00927-z
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DOI: https://doi.org/10.1007/s12145-022-00927-z