Surface wind speed trends and their implication for a highly urbanized Delhi–NCR

Surface wind speed trends for the period of 1981–2020 and their implication for a highly urbanized semi-arid Delhi–NCR and surrounding areas

By Lovish Raheja, Rajvidya Wadalkar, Ranjana Ray Chaudhuri & Arti Pandit

Journal of Earth System Science

Volume 133, article number 112

Published: 05 June 2024

https://doi.org/10.1007/s12040-024-02322-2

Abstract

This study analyses surface wind speed trends over the north Indian region covering Delhi–National Capital Region (NCR) and adjoining areas (lying within latitude 25°–30°N and longitude 75°–80°E) for the recent 40-year period (1981–2020). The analysis reveals an annual stilling of 9.83 × 10−3 m/s/year for the study period. The seasonal analysis indicates the highest stilling in the summer by 14.57 m/s/year in absolute terms. The daytime and night-time wind speed variation analysis revealed a significant difference between daytime and night-time wind speeds over the region. However, declining trends for daytime and night-time wind speeds could not be differentiated statistically, i.e., daytime and night-time speeds had been declining at an almost equal rate over the study period in the study region. Further, the dust concentration analysis revealed a significant rise in dust concentration of 0.72 µg/m3/year; the highest trend has been observed for the winter season. The increase in dust concentration and the stilling together make it a significant concern from a health perspective. The stilling may have further implications on the hydrological cycle, wind energy reliance, and other concerns, which affect the climate at the micro-scale. Rapid urbanisation seems to be the most prominent factor for stilling due to an increase in surface roughness, pointing towards a need for attribute analysis in future. The study further identifies challenges in meteorological studies, which include inherent cyclicity in the meteorological variables (such as wind speed and temperature), parameterisation (choice of the independent variable), the need for sophistication in data retrieval processes, including validation (training and testing) and a lack of adequate understanding about atmospheric phenomena for the region under study. These challenges must be systematically addressed in future research to achieve better and more consistent inferences from meteorological analyses.

https://link.springer.com/article/10.1007/s12040-024-02322-2t content