Accurate fog prediction in densely urbanized cities poses a challenge due to the complex influence of urban morphology on meteorological conditions in the urban roughness sublayer. This study implemented a coupled WRF-Urban Asymmetric Convective Model (WRF-UACM) for Delhi, India, integrating explicit urban physics with Sentinel-updated USGS land-use and urban morphological parameters derived from the UT-GLOBUS dataset. When evaluated against the baseline Asymmetric Convective Model (WRF-BACM) using Winter Fog Experiment (WiFEX) data, WRF-UACM significantly improved urban meteorological variables like diurnal variation of 10-meter wind speed, 2-meter air temperature (T2), and 2-meter relative humidity (RH2) on a fog day. UACM also demonstrates improved accuracy in simulating temperature and a significant reduction in biases for RH2 and wind speed under clear sky conditions. UACM reproduced the nighttime urban heat island effect within the city, showing realistic diurnal heating and cooling patterns that are important for accurate fog onset and duration. UACM effectively predicts the onset, evolution, and dissipation of fog, aligning well with observed data and satellite imagery. Compared to WRF-BACM, WRF-UACM reduces the cold bias soon after the sunset, thus improving the fog onset error by ~4 hours. This study underscores the UACM’s potential in enhancing fog prediction, urging further exploration of various fog types and its application in operational settings, thus offering invaluable insights for preventive measures and mitigating disruptions in urban regions.

Accurate fog prediction in densely urbanized cities poses a challenge due to the complex influence of urban morphology on meteorological conditions in the urban roughness sublayer. This study implemented a coupled WRF-Urban Asymmetric Convective Model (WRF-UACM) for Delhi, India, integrating explicit urban physics with Sentinel-updated USGS land-use and urban morphological parameters derived from the UT-GLOBUS dataset. When evaluated against the baseline Asymmetric Convective Model (WRF-BACM) using Winter Fog Experiment (WiFEX) data, WRF-UACM significantly improved urban meteorological variables like diurnal variation of 10-meter wind speed, 2-meter air temperature (T2), and 2-meter relative humidity (RH2) on a fog day. UACM also demonstrates improved accuracy in simulating temperature and a significant reduction in biases for RH2 and wind speed under clear sky conditions. UACM reproduced the nighttime urban heat island effect within the city, showing realistic diurnal heating and cooling patterns that are important for accurate fog onset and duration. UACM effectively predicts the onset, evolution, and dissipation of fog, aligning well with observed data and satellite imagery. Compared to WRF-BACM, WRF-UACM reduces the cold bias soon after the sunset, thus improving the fog onset error by ~4 hours. This study underscores the UACM’s potential in enhancing fog prediction, urging further exploration of various fog types and its application in operational settings, thus offering invaluable insights for preventive measures and mitigating disruptions in urban regions.

This study attempts to understand the asymmetry in the Indian Summer Monsoon Rainfall (ISMR) response to two types of La Niña whether they evolved from El Niño or La Niña in the previous boreal winter season. It was seen that nine La Niña years during the monsoon season were preceded by El Niño (hereafter ELLA) whereas eight were preceded by La Niña (hereafter LALA) during the period 1961-2021. India received more rainfall during the ELLA years as compared to the LALA years, linked to the difference in the Sea Surface Temperature (SST) and large-scale atmospheric circulation anomalies over the tropical Pacific and Indian oceans. Based on the strength and patterns of the cold SST anomaly and shift in the Walker circulation over the equatorial Pacific Ocean, the enhanced (weakened) convection over the Indian landmass during the ELLA (LALA) years, contributed to more (less) rainfall over India.

We present a very high-resolution (400 m) operational air quality forecasting system developed to alert citizens of Delhi and the National Capital Region (NCR) about acute air pollution episodes. Such a high-resolution system has been developed for the first time and is evaluated during October 2019-February 2020. The system assimilates near real time aerosol observations from in situ and space-borne observations in the WRF-Chem model to produce a 72-h forecast every day in a dynamical downscaling framework. The assimilation of aerosol optical depth and surface PM 2.5 observations improves the initial condition for surface PM 2.5 by about 45 µg/m 3 (about 50%). The accuracy of the forecast degrades slightly with time as mean bias increases from +2.5 µg/m 3 on the first day to-17 µg/m 3 on the third day of forecast. Our forecasts are found to be very capable both for PM 2.5 concentration and unhealthy/ very unhealthy air quality indices categories. 2

This novel study explains a physical mechanism for the rainfall initiation over the southeast peninsular India (SEPI, referred to be a ‘rain shadow’ region) during the southwest monsoon season. Further, the contrasting rainfall patterns between the rain shadow region and central India (CI,) are also elucidated through the response of the maritime continent (MRC) convection. The MRC is found to be a prominent source for the initiation of wet spells over the rain shadow region (during which CI is in dry phase), with the rainfall anomalies over MRC leads SEPI by ~5-7 days. Evolution of convective anomalies resembles a classical Gill-type response, with a pair of Rossby waves on the poleward side of the convection center and Kelvin waves on the eastern side. Thus, the combined effect of large-scale circulation and moisture anomalies over MRC contributes to the preconditioning and subsequent positive rainfall anomalies over the rain shadow region.

Precise understanding of complex physical mechanisms of mesoscale process require high resolution observations of temperature, moisture, wind, precipitation, clouds. Using all collocated observations of microwave radiometer, wind profilers, electric field mill, weather radars over South-East India an observational analysis is conducted for the first time. Analysis suggests that these systems developed in warm, moist environment associated with large-scale low-level convergence. Passage of system is accompanied by convective regions with intense upward motion and towers extending up to higher levels indicating developing phase and presence of upward/downward motion comprising of heavy precipitation representing mature phase of the system followed by stratiform regions with prominent downdraft motion and less precipitation related to decay phase. Large (small) values of reflectivity and cloud liquid water values represent presence of deep (shallow)convective (stratiform) regions. Cloud to Ground (CG) lightning activity associated with storm electrification processes showed the existence of both +CG and –CG flashes in convective and dominant –CG in stratiform regions. Presence of different sized cloud liquid hydrometers in convective regions resulted in bipolar nature due to their collisions however in stratiform regions their distribution is mostly uniform and resulted in single polarity. Combination of different observations has provided the unique opportunity to examine interrelations of different physical mechanisms in storm environment. Inspection of reflectivity, CG lightning and cloud liquid water measurements have demonstrated the relationship of lightning mechanism with storm dynamics and cloud microphysics. Combined investigation of temperature, moisture and wind measurements have given considerable insight of thetae ridge formations resulting from thermal and moisture advections. Isentropic upgliding and downgliding facilitated the unique way to visualize the vertical transport of temperature and moisture through ascent and descent of air parcel. Blend of observations presented considerable insight of synoptic and complex mesoscale processes and their mutual interactions in the storm environment and provided encouraging results in explaining MCS structure.