The National Atmospheric Research Laboratory(NARL) is an autonomous Research Institute funded by the Department of Space of the Government of India. NARL is engaged in fundamental and applied research in the field of Atmospheric Sciences. The research institute was started in 1992 as National Mesosphere-Stratosphere-Troposphere (MST) Radar Facility (NMRF). Over the years many other facilities such as Mie/Rayleigh Lidar, Lower atmospheric wind profiler, optical rain gauge, disdrometer, automated weather stations etc. were added. The NMRF was then expanded into a research institute and renamed as National Atmospheric Research Laboratory on 22 September 2005.
Aerosol-cloud interactions represent the largest uncertainty in climate-change assessment, and while cloud turbulence is considered crucial for droplet growth, its precise role remains unclear. Our laboratory-controlled studies show that turbulence does not always enhance collision and coalescence; instead, its influence emerges only when droplets have a sufficiently broad size distribution. The dissipative-scale droplet behaviour underscores the importance of improved parameterisations to accurately model cloud microphysics.
The mesosphere-lower thermosphere (MLT) region is a highly dynamic region of the atmosphere that is strongly influenced by a broad spectrum of atmospheric waves. Among these, the quasi-two-day wave (QTDW) plays a prominent role in modulating MLT dynamics. In this study, we utilize more than 11 years (November 2013-March 2025) of Sri Venkateswara University (SVU) meteor radar observations made at a low-latitude site (13.63 degrees N, 79.4 degrees E), SVU, Tirupati, India, to investigate the characteristics and impacts of the QTDW, as well as its contribution to momentum and heat transport in the MLT region, which remains poorly understood. The horizontal momentum flux ( zonal heat flux (), and meridional heat flux were analyzed using horizontal winds and the ambipolar diffusion coefficient (derived from meteor decay time). The ambipolar diffusion coefficient, which is directly related to the background temperature, was used for the heat flux estimation. The results reveal distinct seasonal and height-dependent variations. In general, the horizontal momentum flux and zonal heat flux exhibited opposite trends relative to the background zonal mean wind during the solstices above 90 km -positive flux during the winter solstice and negative flux during the summer solstice. The meridional heat flux remained positive throughout, with enhanced values during the solstices and in October. This study is the first to quantify QTDW-induced horizontal momentum and heat fluxes using meteor radar observations over a low-latitude MLT region, providing new insights into wave-mean flow interactions.
In complex systems, events can occur at irregular intervals, and these intervals can encode information about the underlying dynamics of the system. Analyzing the temporal clustering of these events reveals critical insights into the non-random patterns and the temporal evolution. Existing techniques can effectively quantify the overall clustering tendency of events using global statistical measures. However, these macroscopic approaches leave a critical gap, as they do not attempt to investigate the properties of individual clusters. Analyzing individual clusters is essential, as it helps comprehend the local interactions that actively drive the system dynamics, while simultaneously revealing the time scales involved. To address these limitations, we propose a complex network-based framework for analyzing clustering of events occurring at irregular intervals. The framework establishes connections using arrival times, transforming the time series into a network. Network properties are then used to quantify the clustering. Further, a community detection algorithm is used to identify individual clusters in time series. We illustrate the method by applying it to standard arrival processes, such as the Poisson process and the Markov-modulated Poisson process. To further demonstrate its scope, we apply the method to two diverse systems: the time series of droplet arrivals in turbulent flows and the RR intervals in electrocardiogram signals.
The response of radiative, meteorological, fluxes and boundary layer parameters to solar eclipses that occurred in the same season but at different times of the day has been studied using a suite of in-situ (instrumented towers) and remote sensing (SODAR and wind profiler) measurements with a special emphasis on addressing contrasting results from earlier studies. The eclipse on 15 January 2010 occurred in the noon hours, significantly impacting parameters of interest, given above, while the eclipse on 26 December 2019 occurred in the morning hours, concomitantly along with fog, diluting some of the eclipse-induced effects. Nevertheless, during both eclipses, air temperature (T) decreased by 3–4 K around the time of totality, with a varying time lag between the occurrence of totality and the observed temperature minimum. The thermal inertia of the surface layer and the dry soil could be responsible for the delay. The lag is different for different meteorological parameters (T, wind speed, humidity) during both eclipses. The reduction in turbulence intensity caused by decreased insolation reduced the sensible heat flux and also downward transport of momentum, resulting in the reduction in wind speed relative to the reference up to a height of 500 m. No significant change in wind direction is noticed, in contrast to earlier studies. Water vapor pressure decreased in 2010 at the time of the eclipse due to downdrafts and a reduction in evaporation rate, while it increased in 2019 due to fog. Although surface pressure and wind measurements within the boundary layer do not provide direct evidence of gravity waves, the observed increase in variance immediately following the eclipse in both events suggests their presence.
The role of aerosols in climate variability is complex, often leading to changes in cloud vertical structure and posing challenges for precipitation forecasting. This study examines aerosol interactions with mixed-phase clouds, where aerosols act as cloud condensation nuclei (CCN) and ice nuclei (IN), within the temperature range of -20 °C to -40 °C, over Gadanki (13.5oN, 79.2oE), a tropical site in India, using nearly seven years of ground-based, balloon-borne, and satellite remote sensing observations. Lidar-derived aerosol and cloud optical depths (AOD and COD) are used as proxies for aerosol and cloud properties, and their interactions are analyzed through correlation analysis under constraints of ice and liquid water paths (IWP and LWP). The IWP derived from independent radiosonde observations shows moderate to strong correlations with ERA5 and MODIS datasets. COD–AOD correlations across IWP bins (0–25 g/m²) are generally weak, whereas moderate to strong correlations are observed across LWP bins (0–0.4 g/m²), with peaks at 60–90 m and 90–120 m above the cloud base. More pronounced negative COD–AOD correlations are found across IWP bins when low clouds are absent. The extent of significant correlations across IWP bins is highest during the monsoon season, while moderate to strong correlations are observed in the post-monsoon season. This seasonal pattern may reflect changes in the dominant air masses over the region, though further measurements are needed to clarify the underlying aerosol influences.
